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10 GitHub repos with 1,8M+ combined stars ⭐ that replace tools costing $30,000+/year 1. awesome ⭐495k - the list of every other list. Whatever you're looking for, it's here. 2. public-apis ⭐456k - 1,400+ free APIs across 50 categories. Weather, finance, images, games, all documented. 3. scrapling ⭐73.6k -...

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111,774 次观看 • 9 天前 •via X (Twitter)

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11 GitHub repos with 1.5M+ combined stars replace tools you'd otherwise pay $50K+/year for 1. free-for-dev (131k⭐) - hundreds of services with permanent free tiers. No trials, the repo's own rule. 2. public-apis (453k⭐) - 1,500+ free APIs: weather, finance, images, games. 3. awesome-selfhosted (309k⭐)- self-hosted replacements for Notion, Google Photos, Zapier and dozens more subscriptions. 4. awesome-claude-code (51k⭐) - skills, hooks, slash commands, orchestrators for Claude Code. 5. anthropics/skills (165k⭐) - the official skills repo. Start here before third-party ones. 6. awesome-mcp-servers (91k⭐) - thousands of MCP servers connecting your agent to browsers, databases, anything. 7. awesome-llm-apps (116k⭐) - 100+ ready AI agents and RAG apps with full code. 8. system-prompts-and-models-of-ai-tools (142k⭐) - leaked system prompts of Cursor, Devin, v0, Claude Code. 9. awesome-codex-skills (15k⭐) - curated Codex skills sorted by category: data & analytics, writing, productivity, development. 10. awesome (490k⭐) - the list of every other list. Whatever's missing above, it's here. Bookmark this before you pay for something that's already free 👇
1:18

11 GitHub repos with 1.5M+ combined stars replace tools you'd otherwise pay $50K+/year for 1. free-for-dev (131k⭐) - hundreds of services with permanent free tiers. No trials, the repo's own rule. 2. public-apis (453k⭐) - 1,500+ free APIs: weather, finance, images, games. 3. awesome-selfhosted (309k⭐)- self-hosted replacements for Notion, Google Photos, Zapier and dozens more subscriptions. 4. awesome-claude-code (51k⭐) - skills, hooks, slash commands, orchestrators for Claude Code. 5. anthropics/skills (165k⭐) - the official skills repo. Start here before third-party ones. 6. awesome-mcp-servers (91k⭐) - thousands of MCP servers connecting your agent to browsers, databases, anything. 7. awesome-llm-apps (116k⭐) - 100+ ready AI agents and RAG apps with full code. 8. system-prompts-and-models-of-ai-tools (142k⭐) - leaked system prompts of Cursor, Devin, v0, Claude Code. 9. awesome-codex-skills (15k⭐) - curated Codex skills sorted by category: data & analytics, writing, productivity, development. 10. awesome (490k⭐) - the list of every other list. Whatever's missing above, it's here. Bookmark this before you pay for something that's already free 👇

unicode

119,690 次观看 • 24 天前

10 GitHub repos with 560k+ ⭐ combined stars that could save vibe coders $15,000+/year in SaaS bills 1. shadcn/ui ⭐121k - copy-paste components, not a package. What every AI-generated frontend is actually built on now. 2. supabase ⭐108k - Firebase alternative that's actually free to start. Auth, DB, storage in one Claude Code prompt. 3.open-design ⭐84.5k - open-source Claude Design alternative. Your coding agent becomes the design engine. 4. awesome-ai-agents ⭐29k - every agent framework and no-code builder in one list, ranked by what people actually ship. 5. awesome-generative-ai-apps ⭐3k - 50+ open-source AI apps you can clone, deploy, and monetize instead of paying $30-50/mo for the SaaS version. 6. medusa ⭐35k - full ecommerce backend, open source. Skip Shopify Plus fees entirely on your next vibe-coded store. 7. appwrite ⭐57k - complete backend-as-a-service, self-hosted. Auth, DB, functions, storage, one prompt away from Firebase money. 8. chatwoot ⭐35k - customer support platform, self-hosted. Replaces Intercom/Zendesk seats running $100+/agent/month. 9. nocodb ⭐64k - turns any database into an Airtable-style interface. 10. activepieces ⭐23k - open-source Zapier alternative built for AI workflows. Automate without the per-task pricing. Save this before you pay for another tool this repo already replaces for free 👇
1:03

10 GitHub repos with 560k+ ⭐ combined stars that could save vibe coders $15,000+/year in SaaS bills 1. shadcn/ui ⭐121k - copy-paste components, not a package. What every AI-generated frontend is actually built on now. 2. supabase ⭐108k - Firebase alternative that's actually free to start. Auth, DB, storage in one Claude Code prompt. 3.open-design ⭐84.5k - open-source Claude Design alternative. Your coding agent becomes the design engine. 4. awesome-ai-agents ⭐29k - every agent framework and no-code builder in one list, ranked by what people actually ship. 5. awesome-generative-ai-apps ⭐3k - 50+ open-source AI apps you can clone, deploy, and monetize instead of paying $30-50/mo for the SaaS version. 6. medusa ⭐35k - full ecommerce backend, open source. Skip Shopify Plus fees entirely on your next vibe-coded store. 7. appwrite ⭐57k - complete backend-as-a-service, self-hosted. Auth, DB, functions, storage, one prompt away from Firebase money. 8. chatwoot ⭐35k - customer support platform, self-hosted. Replaces Intercom/Zendesk seats running $100+/agent/month. 9. nocodb ⭐64k - turns any database into an Airtable-style interface. 10. activepieces ⭐23k - open-source Zapier alternative built for AI workflows. Automate without the per-task pricing. Save this before you pay for another tool this repo already replaces for free 👇

unicode

47,548 次观看 • 13 天前

10 GitHub repos with ⭐ 1.2M+ combined stars that help you build your AI agent from scratch 1. n8n 201k⭐ - visual agent builder with 400+ integrations. Wire up multi-step AI workflows without writing a backend. 2. Hermes Agent 231k⭐ - the fastest-growing open-source agent framework of 2026. Self-improving skill loop, persistent memory across sessions. 3. Dify 152k⭐ - visual builder for agentic workflows and RAG pipelines, production-ready out of the box. 4. LangChain 144k⭐ - the standard framework for LLM apps. Chains, agents, retrieval, all in one place. 5. MetaGPT 70k⭐ - simulates an entire software company. PM, architect, engineer agents that build your app together. 6. AutoGen 60k⭐ - Microsoft's framework for multi-agent conversations and coordination. 7. OpenCode 198k⭐ - terminal coding agent, provider-agnostic across 75+ models. The go-to harness for agentic coding in 2026. 8. LlamaIndex 52k⭐ - connects your agents to your actual data. Indexing and retrieval done right. 9. CrewAI 57k⭐ - role-based crews of agents. Reads almost like plain English, no graph to learn. 10. LangGraph 40k⭐ - graph-based orchestration when you need precise control over agent state in production. Save this before you pay for another agent-building course 👇
1:08

10 GitHub repos with ⭐ 1.2M+ combined stars that help you build your AI agent from scratch 1. n8n 201k⭐ - visual agent builder with 400+ integrations. Wire up multi-step AI workflows without writing a backend. 2. Hermes Agent 231k⭐ - the fastest-growing open-source agent framework of 2026. Self-improving skill loop, persistent memory across sessions. 3. Dify 152k⭐ - visual builder for agentic workflows and RAG pipelines, production-ready out of the box. 4. LangChain 144k⭐ - the standard framework for LLM apps. Chains, agents, retrieval, all in one place. 5. MetaGPT 70k⭐ - simulates an entire software company. PM, architect, engineer agents that build your app together. 6. AutoGen 60k⭐ - Microsoft's framework for multi-agent conversations and coordination. 7. OpenCode 198k⭐ - terminal coding agent, provider-agnostic across 75+ models. The go-to harness for agentic coding in 2026. 8. LlamaIndex 52k⭐ - connects your agents to your actual data. Indexing and retrieval done right. 9. CrewAI 57k⭐ - role-based crews of agents. Reads almost like plain English, no graph to learn. 10. LangGraph 40k⭐ - graph-based orchestration when you need precise control over agent state in production. Save this before you pay for another agent-building course 👇

unicode

30,063 次观看 • 6 天前

10 GitHub repos with ⭐ 450k+ combined stars that stop your agent from wasting tokens 1. caveman 98k⭐ - makes your AI agent talk like a caveman. Same answers, 65% fewer output tokens. 2. rtk 76k⭐ - CLI proxy that filters git/test/docker output before it hits your context. Up to 90% less bash noise. 3. mem0 63k⭐ - memory layer for AI agents. Stops your agent from re-explaining the same context every session. 4. context7 60.7k⭐ - pulls exact, up-to-date docs into context instead of your agent guessing and burning tokens on retries. 5. aider 48k⭐ - builds a map of your repo instead of loading the whole codebase into context. 6. code-review-graph 30k⭐ - graphs your codebase so your agent reads 2-3 files instead of the whole repo. Up to 376x fewer tokens per question. 7. serena 28k⭐ - gives agents symbol-level code access instead of reading full files line by line. 8. repomix 28k⭐ - compresses your entire repo into an AI-friendly format. ~70% token reduction. 9. ccusage 18k⭐ - shows you exactly where your Claude Code sessions are burning tokens. 10. GPTCache 8k⭐ - semantic cache for LLM calls. Stop paying twice for the same question. Save this before your next agent session burns through your subscription 👇
1:03

10 GitHub repos with ⭐ 450k+ combined stars that stop your agent from wasting tokens 1. caveman 98k⭐ - makes your AI agent talk like a caveman. Same answers, 65% fewer output tokens. 2. rtk 76k⭐ - CLI proxy that filters git/test/docker output before it hits your context. Up to 90% less bash noise. 3. mem0 63k⭐ - memory layer for AI agents. Stops your agent from re-explaining the same context every session. 4. context7 60.7k⭐ - pulls exact, up-to-date docs into context instead of your agent guessing and burning tokens on retries. 5. aider 48k⭐ - builds a map of your repo instead of loading the whole codebase into context. 6. code-review-graph 30k⭐ - graphs your codebase so your agent reads 2-3 files instead of the whole repo. Up to 376x fewer tokens per question. 7. serena 28k⭐ - gives agents symbol-level code access instead of reading full files line by line. 8. repomix 28k⭐ - compresses your entire repo into an AI-friendly format. ~70% token reduction. 9. ccusage 18k⭐ - shows you exactly where your Claude Code sessions are burning tokens. 10. GPTCache 8k⭐ - semantic cache for LLM calls. Stop paying twice for the same question. Save this before your next agent session burns through your subscription 👇

unicode

65,080 次观看 • 7 天前

10 GitHub repos with 637k+ ⭐️ combined stars that save vibe coders $20,000+/year in SaaS bills 1. infisical ⭐️ 28.7k - secrets, API keys, and access all in one place with encryption and audit logs. Skip this and your .env eventually leaks into a public repo along with your bill. 2. shadcn/improve ⭐️ 8.8k - your expensive model audits the codebase and writes the plan, a cheap model executes it. 3. trigger dev ⭐️ 16k - background jobs and AI agents with no timeouts and no per-run billing. 4. n8n ⭐️ 200k - visual automation with native AI agents. Replaces Zapier/Make entirely, self-hosted. 5. pocketbase ⭐️ 60k - your entire backend in one file: SQLite, auth, realtime, file storage. Replaces Firebase for solo projects, no monthly bill. 6. coolify ⭐️ 60.4k - self-hosted PaaS, alternative to Vercel/Heroku/Netlify. Deploy to your own VPS with one script, no function limits. 7. dify ⭐️ 152k - visual builder for AI agents and RAG pipelines. Skip the $500/mo no-code AI builder subscription. 8. posthog ⭐️ 37k - product analytics, session replay, feature flags, A/B testing, self-hosted. Replaces Mixpanel + LaunchDarkly combined. 9. metabase ⭐️ 48.7k - BI and dashboards without a Looker/Tableau license. Point it at your DB and ship charts today. 10. zulip ⭐️ 25.6k - threaded team chat, self-hosted. Replaces Slack's paid tier once your team grows. Save this before you pay for another tool this list already replaces for free 👇
1:07

10 GitHub repos with 637k+ ⭐️ combined stars that save vibe coders $20,000+/year in SaaS bills 1. infisical ⭐️ 28.7k - secrets, API keys, and access all in one place with encryption and audit logs. Skip this and your .env eventually leaks into a public repo along with your bill. 2. shadcn/improve ⭐️ 8.8k - your expensive model audits the codebase and writes the plan, a cheap model executes it. 3. trigger dev ⭐️ 16k - background jobs and AI agents with no timeouts and no per-run billing. 4. n8n ⭐️ 200k - visual automation with native AI agents. Replaces Zapier/Make entirely, self-hosted. 5. pocketbase ⭐️ 60k - your entire backend in one file: SQLite, auth, realtime, file storage. Replaces Firebase for solo projects, no monthly bill. 6. coolify ⭐️ 60.4k - self-hosted PaaS, alternative to Vercel/Heroku/Netlify. Deploy to your own VPS with one script, no function limits. 7. dify ⭐️ 152k - visual builder for AI agents and RAG pipelines. Skip the $500/mo no-code AI builder subscription. 8. posthog ⭐️ 37k - product analytics, session replay, feature flags, A/B testing, self-hosted. Replaces Mixpanel + LaunchDarkly combined. 9. metabase ⭐️ 48.7k - BI and dashboards without a Looker/Tableau license. Point it at your DB and ship charts today. 10. zulip ⭐️ 25.6k - threaded team chat, self-hosted. Replaces Slack's paid tier once your team grows. Save this before you pay for another tool this list already replaces for free 👇

unicode

39,573 次观看 • 10 天前

Excited to share our new project 🦉OWL - an open-source alternative to Manus AI with 6K+ stars and climbing… 🦉OWL: Everyone’s talking about Manus AI (an agent that can research, browse, code, and automate tasks.) But there’s a catch: → All the above agents cost $20 to $200 a month → Manus AI is available via an invite code only OWL by CAMEL-AI is an opensource project that’s breaking records: ⭐ 6K+ GitHub stars in 2 days 🏆 Ranks #1 on the GAIA Benchmark among open-source projects with a 58.18 avg score! 📌 Specialized Multi-Agent Collaboration ↳ AI user agents break down complex tasks ↳ Assistants agents create detailed execution strategies and interact with tools and tool agents ↳ Tools / Tool agents interface with external services and APIs 📌 Real-World Capabilities ↳ Autonomous research, coding, and web browsing ↳ Runs locally on your machine for privacy ↳ Supports top LLMs (easily integrated with GPT-4O, Claude 3.7, Gemini, Mistral, DeepSeek , Qwen, Ollama, Groq more) ↳ Automates complex workflows, from research to execution I 📌 Simple Setup ↳ Fast installs via conda or uv ↳ Docker support for easy deployment ↳ Straightforward config with TOML files No restrictions. No invites. No paywalls. Just powerful multi-agent collaboration. AI autonomy shouldn’t be locked behind paywalls.
1:21

Excited to share our new project 🦉OWL - an open-source alternative to Manus AI with 6K+ stars and climbing… 🦉OWL: Everyone’s talking about Manus AI (an agent that can research, browse, code, and automate tasks.) But there’s a catch: → All the above agents cost $20 to $200 a month → Manus AI is available via an invite code only OWL by CAMEL-AI is an opensource project that’s breaking records: ⭐ 6K+ GitHub stars in 2 days 🏆 Ranks #1 on the GAIA Benchmark among open-source projects with a 58.18 avg score! 📌 Specialized Multi-Agent Collaboration ↳ AI user agents break down complex tasks ↳ Assistants agents create detailed execution strategies and interact with tools and tool agents ↳ Tools / Tool agents interface with external services and APIs 📌 Real-World Capabilities ↳ Autonomous research, coding, and web browsing ↳ Runs locally on your machine for privacy ↳ Supports top LLMs (easily integrated with GPT-4O, Claude 3.7, Gemini, Mistral, DeepSeek , Qwen, Ollama, Groq more) ↳ Automates complex workflows, from research to execution I 📌 Simple Setup ↳ Fast installs via conda or uv ↳ Docker support for easy deployment ↳ Straightforward config with TOML files No restrictions. No invites. No paywalls. Just powerful multi-agent collaboration. AI autonomy shouldn’t be locked behind paywalls.

Guohao Li 🐫

223,252 次观看 • 1 年前

Building AI agents and tools is getting ridiculously easy! Here is a pretty impressive FREE and Open-Source AI agent builder that runs on your computer. It's a desktop app you can install on Mac or Windows. Link: • Free • 100% no-code: You can type what you want, and the tool will build everything for you. • You can use local models like DeepSeek or Qwen, or connect to cloud models like GPT-4o, Claude, or Gemini with your API key. • You can turn the tools you build into MCP Servers. I recorded a quick video to show you how easy it is to build something from scratch.
4:10

Building AI agents and tools is getting ridiculously easy! Here is a pretty impressive FREE and Open-Source AI agent builder that runs on your computer. It's a desktop app you can install on Mac or Windows. Link: • Free • 100% no-code: You can type what you want, and the tool will build everything for you. • You can use local models like DeepSeek or Qwen, or connect to cloud models like GPT-4o, Claude, or Gemini with your API key. • You can turn the tools you build into MCP Servers. I recorded a quick video to show you how easy it is to build something from scratch.

Santiago

56,815 次观看 • 1 年前

10 repos blowing up on GitHub this week that replace $1,500/month in AI tools 1. andrej-karpathy-skills → replaces paid Claude Code courses one CLAUDE.md file from Karpathy's LLM coding observations 48,965 stars. 7,939 stars TODAY 2. claude-mem → replaces paid context/memory tools auto-captures everything Claude does across sessions compresses with AI and injects into future sessions 59,373 stars. 1,907 stars today 3. voicebox → replaces ElevenLabs ($22/mo) open-source voice synthesis studio 18,963 stars. 887 stars today 4. open-agents → replaces paid agent platforms ($200/mo) open-source template for building cloud agents. by Vercel 3,105 stars. 735 stars today 5. cognee → replaces paid knowledge bases ($50/mo) AI agent memory engine in 6 lines of code 15,733 stars 6. magika → replaces paid file detection tools AI file content type detection. by Google 14,603 stars 7. GenericAgent → replaces paid agent infra ($100/mo) self-evolving agent. grows skill tree from 3.3K-line seed 6x less token consumption than standard agents 2,661 stars. 883 stars today 8. omi → replaces Rewind AI ($25/mo) AI that sees your screen + listens to conversations tells you what to do next 8,952 stars. 488 stars today 9. evolver → replaces manual agent optimization self-evolution engine for AI agents genome evolution protocol 3,074 stars. 866 stars today 10. wallet tracking + copy trading → Kreo tracks top Polymarket wallets. auto copies trades the only tool on this list i actually pay for because it makes more than it costs → total before: ~$1,500/month in AI subscriptions total now: $0 + Kreo like + bookmark you'll need this
1:05

10 repos blowing up on GitHub this week that replace $1,500/month in AI tools 1. andrej-karpathy-skills → replaces paid Claude Code courses one CLAUDE.md file from Karpathy's LLM coding observations 48,965 stars. 7,939 stars TODAY 2. claude-mem → replaces paid context/memory tools auto-captures everything Claude does across sessions compresses with AI and injects into future sessions 59,373 stars. 1,907 stars today 3. voicebox → replaces ElevenLabs ($22/mo) open-source voice synthesis studio 18,963 stars. 887 stars today 4. open-agents → replaces paid agent platforms ($200/mo) open-source template for building cloud agents. by Vercel 3,105 stars. 735 stars today 5. cognee → replaces paid knowledge bases ($50/mo) AI agent memory engine in 6 lines of code 15,733 stars 6. magika → replaces paid file detection tools AI file content type detection. by Google 14,603 stars 7. GenericAgent → replaces paid agent infra ($100/mo) self-evolving agent. grows skill tree from 3.3K-line seed 6x less token consumption than standard agents 2,661 stars. 883 stars today 8. omi → replaces Rewind AI ($25/mo) AI that sees your screen + listens to conversations tells you what to do next 8,952 stars. 488 stars today 9. evolver → replaces manual agent optimization self-evolution engine for AI agents genome evolution protocol 3,074 stars. 866 stars today 10. wallet tracking + copy trading → Kreo tracks top Polymarket wallets. auto copies trades the only tool on this list i actually pay for because it makes more than it costs → total before: ~$1,500/month in AI subscriptions total now: $0 + Kreo like + bookmark you'll need this

self.dll

361,846 次观看 • 4 个月前

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!
2:43

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

Andrew Ng

142,137 次观看 • 1 年前

these 5 GitHub repos replaced my $2,400/month trading setup you're spending thousands on software anyone can fork the repos behind those tools are sitting on GitHub for free here's what i actually run: 1. fredapi (1K ★) Bloomberg charges $2,000/mo for macro data this pulls every Fed dataset into Python with one API key GDP, CPI, rates, employment - pair it with Claude and you're set /// 2. ccxt (42K ★) i was paying $50/mo per exchange just for API access ccxt connects 107 exchanges through one interface JS; Python; PHP; Go; C# the industry standard since day one /// 3. freqtrade (47K ★) killed my $200/mo bot subscription in one afternoon backtesting, hyperopt, FreqAI, live on 20+ exchanges 7 years of weekly commits. Telegram control. your strategies stay yours /// 4. OpenBB (40K ★) equities, options, crypto, fixed income, macro - one terminal plugs into Python, Excel, REST API, MCP for AI agents my $500/mo data feed couldn't do half of this /// 5. goose (40K ★) by Block (Jack Dorsey). Rust. Apache 2.0 full AI coding agent. any LLM. 3,000+ MCP tools. runs locally the $200/mo i was spending on Claude Code now costs me $0 /// bookmark this and thank me later
0:57

these 5 GitHub repos replaced my $2,400/month trading setup you're spending thousands on software anyone can fork the repos behind those tools are sitting on GitHub for free here's what i actually run: 1. fredapi (1K ★) Bloomberg charges $2,000/mo for macro data this pulls every Fed dataset into Python with one API key GDP, CPI, rates, employment - pair it with Claude and you're set /// 2. ccxt (42K ★) i was paying $50/mo per exchange just for API access ccxt connects 107 exchanges through one interface JS; Python; PHP; Go; C# the industry standard since day one /// 3. freqtrade (47K ★) killed my $200/mo bot subscription in one afternoon backtesting, hyperopt, FreqAI, live on 20+ exchanges 7 years of weekly commits. Telegram control. your strategies stay yours /// 4. OpenBB (40K ★) equities, options, crypto, fixed income, macro - one terminal plugs into Python, Excel, REST API, MCP for AI agents my $500/mo data feed couldn't do half of this /// 5. goose (40K ★) by Block (Jack Dorsey). Rust. Apache 2.0 full AI coding agent. any LLM. 3,000+ MCP tools. runs locally the $200/mo i was spending on Claude Code now costs me $0 /// bookmark this and thank me later

Hanako

54,923 次观看 • 4 个月前

5 open-source AI repos that blew up on github this week → 1. MinerU (opendatalab) - ~69k★ turns any PDF or office doc into clean, LLM-ready markdown - the fix for garbage RAG inputs 2. voicebox (jamiepine) - ~35k★ open-source AI voice studio - clone a voice, dictate, create. the local ElevenLabs 3. ai-website-cloner-template (JCodesMore) - ~22k★ clone any website with one command using your AI coding agent - great for learning and prototyping 4. Anthropic-Cybersecurity-Skills (mukul975) - ~21k★ 800+ ready security skills for AI agents, mapped to MITRE ATT&CK and NIST - works with claude code, cursor, codex 5. agent-native (builderio) - ~3k★ a framework for building apps designed for AI agents from day one, not bolted on after one of these saves you a paid tool. bookmark before you forge
0:59

5 open-source AI repos that blew up on github this week → 1. MinerU (opendatalab) - ~69k★ turns any PDF or office doc into clean, LLM-ready markdown - the fix for garbage RAG inputs 2. voicebox (jamiepine) - ~35k★ open-source AI voice studio - clone a voice, dictate, create. the local ElevenLabs 3. ai-website-cloner-template (JCodesMore) - ~22k★ clone any website with one command using your AI coding agent - great for learning and prototyping 4. Anthropic-Cybersecurity-Skills (mukul975) - ~21k★ 800+ ready security skills for AI agents, mapped to MITRE ATT&CK and NIST - works with claude code, cursor, codex 5. agent-native (builderio) - ~3k★ a framework for building apps designed for AI agents from day one, not bolted on after one of these saves you a paid tool. bookmark before you forge

self.dll

65,079 次观看 • 1 个月前

most traders pay $3,000+/month for tools GitHub replaced for free. 9 repos. zero subscriptions. 1. OpenBB → replaces Bloomberg Terminal ($2,000/mo) financial data platform built for AI agents and quants connects natively to claude via MCP. most people don't know this. 2. freqtrade → replaces paid crypto bot services ($100/mo) ML strategy optimization. runs on binance, bybit, hyperliquid and 10+ others 34,000 stars. free and always will be. 3. hummingbot → replaces HFT bot platforms ($200/mo) $34B+ in user-generated trading volume has a native claude MCP integration. connect your AI directly to 140+ exchanges. 4. FinGPT → replaces financial AI subscriptions ($150/mo) open-source LLMs that outperform GPT-4 on market sentiment bloomberg spent $3M training theirs. this costs $17 to fine-tune. 5. NautilusTrader → replaces institutional trading platforms ($500/mo) production-grade. rust-native. fast enough to train RL trading agents same codebase for backtesting and live. zero rewrite needed. 6. QuantConnect Lean → replaces paid quant research platforms ($100/mo) professional algo trading engine. python + C# from backtest to live in one click. used by 200K+ quants worldwide. 7. jesse → replaces TradingView algo subscriptions ($25/mo) advanced crypto trading framework for serious strategy builders clean. powerful. no bloat. 8. vectorbt → replaces paid backtesting tools ($80/mo) fastest backtesting library in existence tests thousands of strategies in seconds. pandas-based. 9. FinRL → replaces custom AI trading infrastructure ($300/mo) financial reinforcement learning. train your own trading AI. from the same team behind FinGPT. 10. AlphaCartel Setup → replaces hedge fund signal services ($300/mo) this is where all 9 repos above connect into one working system claude-powered bots. live signals. no-code setup. community of traders already printing. total before: ~$3,455/month total now: $0 + alphacartel like + bookmark. you'll need this.
0:58

most traders pay $3,000+/month for tools GitHub replaced for free. 9 repos. zero subscriptions. 1. OpenBB → replaces Bloomberg Terminal ($2,000/mo) financial data platform built for AI agents and quants connects natively to claude via MCP. most people don't know this. 2. freqtrade → replaces paid crypto bot services ($100/mo) ML strategy optimization. runs on binance, bybit, hyperliquid and 10+ others 34,000 stars. free and always will be. 3. hummingbot → replaces HFT bot platforms ($200/mo) $34B+ in user-generated trading volume has a native claude MCP integration. connect your AI directly to 140+ exchanges. 4. FinGPT → replaces financial AI subscriptions ($150/mo) open-source LLMs that outperform GPT-4 on market sentiment bloomberg spent $3M training theirs. this costs $17 to fine-tune. 5. NautilusTrader → replaces institutional trading platforms ($500/mo) production-grade. rust-native. fast enough to train RL trading agents same codebase for backtesting and live. zero rewrite needed. 6. QuantConnect Lean → replaces paid quant research platforms ($100/mo) professional algo trading engine. python + C# from backtest to live in one click. used by 200K+ quants worldwide. 7. jesse → replaces TradingView algo subscriptions ($25/mo) advanced crypto trading framework for serious strategy builders clean. powerful. no bloat. 8. vectorbt → replaces paid backtesting tools ($80/mo) fastest backtesting library in existence tests thousands of strategies in seconds. pandas-based. 9. FinRL → replaces custom AI trading infrastructure ($300/mo) financial reinforcement learning. train your own trading AI. from the same team behind FinGPT. 10. AlphaCartel Setup → replaces hedge fund signal services ($300/mo) this is where all 9 repos above connect into one working system claude-powered bots. live signals. no-code setup. community of traders already printing. total before: ~$3,455/month total now: $0 + alphacartel like + bookmark. you'll need this.

AI Bulls

107,531 次观看 • 4 个月前

🚨 Claude Code costs $200/month. GitHub Copilot costs $19/month. Jack Dorsey's company built a free alternative. 35,000 GitHub stars. It's called Goose. An open source AI agent built by Block that goes beyond code suggestions. It installs, executes, edits, and tests. With any LLM you choose. Not autocomplete. Not suggestions. A full autonomous agent that takes actions on your computer. No vendor lock-in. No monthly subscription. Bring your own model. Here's what Goose does: → Works with ANY LLM. Claude, GPT, Gemini, Llama, DeepSeek, Ollama. Your choice. → Reads and understands your entire codebase → Writes, edits, and refactors code across multiple files → Runs shell commands and installs dependencies → Executes and debugs your code automatically → Extensible through MCP. Connect it to any external tool. → Desktop app, CLI, and web interface. Pick your workflow. → Written in Rust. Fast. Lightweight. No bloat. Here's the wildest part: Block is a $40 billion company. They built Cash App, Square, and TIDAL. They use Goose internally. Then they open sourced the entire thing. This isn't a side project from a random developer. This is production-grade tooling from a company that processes billions in payments. Built for their own engineers. Given to everyone. Claude Code: $200/month. Locked to Claude. GitHub Copilot: $19/month. Locked to GitHub. Cursor: $20/month. Locked to their editor. Goose: Free. Any LLM. Any editor. Any workflow. Forever. 35.3K GitHub stars. 3.3K forks. 4,078 commits. Built by Block. 100% Open Source. Apache 2.0 License.
1:49

🚨 Claude Code costs $200/month. GitHub Copilot costs $19/month. Jack Dorsey's company built a free alternative. 35,000 GitHub stars. It's called Goose. An open source AI agent built by Block that goes beyond code suggestions. It installs, executes, edits, and tests. With any LLM you choose. Not autocomplete. Not suggestions. A full autonomous agent that takes actions on your computer. No vendor lock-in. No monthly subscription. Bring your own model. Here's what Goose does: → Works with ANY LLM. Claude, GPT, Gemini, Llama, DeepSeek, Ollama. Your choice. → Reads and understands your entire codebase → Writes, edits, and refactors code across multiple files → Runs shell commands and installs dependencies → Executes and debugs your code automatically → Extensible through MCP. Connect it to any external tool. → Desktop app, CLI, and web interface. Pick your workflow. → Written in Rust. Fast. Lightweight. No bloat. Here's the wildest part: Block is a $40 billion company. They built Cash App, Square, and TIDAL. They use Goose internally. Then they open sourced the entire thing. This isn't a side project from a random developer. This is production-grade tooling from a company that processes billions in payments. Built for their own engineers. Given to everyone. Claude Code: $200/month. Locked to Claude. GitHub Copilot: $19/month. Locked to GitHub. Cursor: $20/month. Locked to their editor. Goose: Free. Any LLM. Any editor. Any workflow. Forever. 35.3K GitHub stars. 3.3K forks. 4,078 commits. Built by Block. 100% Open Source. Apache 2.0 License.

Nav Toor

393,720 次观看 • 4 个月前

A basic VPS runs $20-40 a month at most providers. This GitHub README has been telling people how to get the same thing for $0 since 2015. > It's called free-for-dev. 132k stars, still maintained daily, 1600+ people adding new free tiers and killing dead ones every week. Not 14-day trials. The rule: if it's not free for at least a year, it doesn't make the list. Inside: → Oracle Cloud - 2 servers, 12GB RAM, free forever, no time limit → AWS Lambda - run code 1 million times a month before you pay a cent → Cloudflare - unlimited websites, DNS, SSL, and a global CDN, free → Google Cloud Run - 2 million requests a month on the house One rule they never break: if the security certificate isn't free too, it gets deleted from the list. Every side project starts with the same 20 minutes of Googling "is this actually free." This repo already did that search for you, and keeps redoing it every week. Bookmark it before your next project makes you do that search all over again.
1:44

A basic VPS runs $20-40 a month at most providers. This GitHub README has been telling people how to get the same thing for $0 since 2015. > It's called free-for-dev. 132k stars, still maintained daily, 1600+ people adding new free tiers and killing dead ones every week. Not 14-day trials. The rule: if it's not free for at least a year, it doesn't make the list. Inside: → Oracle Cloud - 2 servers, 12GB RAM, free forever, no time limit → AWS Lambda - run code 1 million times a month before you pay a cent → Cloudflare - unlimited websites, DNS, SSL, and a global CDN, free → Google Cloud Run - 2 million requests a month on the house One rule they never break: if the security certificate isn't free too, it gets deleted from the list. Every side project starts with the same 20 minutes of Googling "is this actually free." This repo already did that search for you, and keeps redoing it every week. Bookmark it before your next project makes you do that search all over again.

Atenov int.

142,386 次观看 • 1 天前

If your MCP server has dozens of tools, it’s probably built wrong. You need tools that are specific and clear for each use case—but you also can’t have too many. This creates an almost impossible tradeoff that most companies don’t know how to solve. That’s why I interviewed my friend Alex Rattray (Alex Rattray), the founder and CEO of Stainless. Stainless builds APIs, SDKs, and MCP servers for companies like OpenAI and Anthropic. Alex has spent years mastering how to make software talk to software, and he came on the show to share what he knows. I had him on Every 📧’s AI & I to talk about MCP and the future of the AI-native internet. We get into: • Design MCP servers to be lean and precise. Alex’s best practices for building reliable MCP servers start with keeping the toolset small, giving each tool a precise name and description, and minimizing the inputs and outputs the model has to handle. At Stainless, they also often add a JSON filter on top to strip out unnecessary data. • Make complex APIs manageable with dynamic mode. To solve the problem of how an AI figures out which tool to use in larger APIs, Stainless switches to “dynamic mode,” where the model gets only three tools: List the endpoints, pick one and learn about it, and then execute it. • MCP servers as business copilots. At Stainless, Alex uses MCP servers to connect tools like Notion and HubSpot, so he can ask questions like, “Which customers signed up last week?” The system queries multiple databases and returns a summary that would’ve otherwise taken multiple logins and searches. • Create a “brain” for your company with Claude Code. Alex built a shared company brain at Stainless by keeping Claude Code running on his system and asking it to save useful inputs—like customer feedback and SQL queries—into GitHub. Over time, this creates a curated archive his team can query easily. • The future of MCP is code execution. Instead of giving models hundreds of tools, Alex believes the most powerful setup will be a simple code execution tool and a doc search tool. The AI writes code against an API’s SDK, runs it on a server, and checks the docs when it gets stuck. This is a must-watch for anyone who wants to understand MCP—and learn how to use them as a competitive edge. Watch below! Timestamps: Introduction: 00:01:14 Why Alex likes running barefoot: 00:02:54 APIs and MCP, the connectors of the new internet: 00:05:09 Why MCP servers are hard to get right: 00:10:53 Design principles for reliable MCP servers: 00:20:07 Scaling MCP servers for large APIs: 00:23:50 Using MCP for business ops at Stainless: 00:25:14 Building a company brain with Claude Code: 00:28:12 Where MCP goes from here: 00:33:59 Alex’s take on the security model for MCP: 00:41:10
51:39

If your MCP server has dozens of tools, it’s probably built wrong. You need tools that are specific and clear for each use case—but you also can’t have too many. This creates an almost impossible tradeoff that most companies don’t know how to solve. That’s why I interviewed my friend Alex Rattray (Alex Rattray), the founder and CEO of Stainless. Stainless builds APIs, SDKs, and MCP servers for companies like OpenAI and Anthropic. Alex has spent years mastering how to make software talk to software, and he came on the show to share what he knows. I had him on Every 📧’s AI & I to talk about MCP and the future of the AI-native internet. We get into: • Design MCP servers to be lean and precise. Alex’s best practices for building reliable MCP servers start with keeping the toolset small, giving each tool a precise name and description, and minimizing the inputs and outputs the model has to handle. At Stainless, they also often add a JSON filter on top to strip out unnecessary data. • Make complex APIs manageable with dynamic mode. To solve the problem of how an AI figures out which tool to use in larger APIs, Stainless switches to “dynamic mode,” where the model gets only three tools: List the endpoints, pick one and learn about it, and then execute it. • MCP servers as business copilots. At Stainless, Alex uses MCP servers to connect tools like Notion and HubSpot, so he can ask questions like, “Which customers signed up last week?” The system queries multiple databases and returns a summary that would’ve otherwise taken multiple logins and searches. • Create a “brain” for your company with Claude Code. Alex built a shared company brain at Stainless by keeping Claude Code running on his system and asking it to save useful inputs—like customer feedback and SQL queries—into GitHub. Over time, this creates a curated archive his team can query easily. • The future of MCP is code execution. Instead of giving models hundreds of tools, Alex believes the most powerful setup will be a simple code execution tool and a doc search tool. The AI writes code against an API’s SDK, runs it on a server, and checks the docs when it gets stuck. This is a must-watch for anyone who wants to understand MCP—and learn how to use them as a competitive edge. Watch below! Timestamps: Introduction: 00:01:14 Why Alex likes running barefoot: 00:02:54 APIs and MCP, the connectors of the new internet: 00:05:09 Why MCP servers are hard to get right: 00:10:53 Design principles for reliable MCP servers: 00:20:07 Scaling MCP servers for large APIs: 00:23:50 Using MCP for business ops at Stainless: 00:25:14 Building a company brain with Claude Code: 00:28:12 Where MCP goes from here: 00:33:59 Alex’s take on the security model for MCP: 00:41:10

Dan Shipper 📧

15,645 次观看 • 10 个月前

Building an Agent Team on Buzz (Complete Guide) Buzz is a new free platform, that feels exactly like Slack, except the agents aren't add ons, they are equals. and in 5 minutes you can create an agent team. And it works with your existing Codex and Claude Code subscriptions... So it's free to use. This video is divided into 2 parts: --- ⭐ Part 1 Conversation with Vinny (Vinny) 00:00 Introduction 01:59 Why is Buzz Going Viral? 07:08 Creating Agents & Channels with Fizz 20:03 Adding Other Harnesses (OpenCode, Cursor) 21:25 The Buzz Mobile App 22:36 Payments & Shared Compute 25:36 Workflows & Projects: A GitHub Killer? 30:14 The Future of Buzz: An Open Cowork? 35:13 Automations, Triggers & Trusting Your Agents --- ⭐ Part 2 - Getting Started Tutorial (My workflow) 42:32 Tutorial and Breakdown 43:03 Downloading Buzz And Default Agents 43:35 Creating your first agent 45:13 Adding Agents to channels 45:43 Why I use Codex as Lead Agent 47:06 Using Codex, Claude Code and Grok for task 48:52 Adding Muse (Meta Model) using OpenRouter 51:23 iOS app is Free and easy to use 51:50 My management Channel (My #1 use case) ---
55:15

Building an Agent Team on Buzz (Complete Guide) Buzz is a new free platform, that feels exactly like Slack, except the agents aren't add ons, they are equals. and in 5 minutes you can create an agent team. And it works with your existing Codex and Claude Code subscriptions... So it's free to use. This video is divided into 2 parts: --- ⭐ Part 1 Conversation with Vinny (Vinny) 00:00 Introduction 01:59 Why is Buzz Going Viral? 07:08 Creating Agents & Channels with Fizz 20:03 Adding Other Harnesses (OpenCode, Cursor) 21:25 The Buzz Mobile App 22:36 Payments & Shared Compute 25:36 Workflows & Projects: A GitHub Killer? 30:14 The Future of Buzz: An Open Cowork? 35:13 Automations, Triggers & Trusting Your Agents --- ⭐ Part 2 - Getting Started Tutorial (My workflow) 42:32 Tutorial and Breakdown 43:03 Downloading Buzz And Default Agents 43:35 Creating your first agent 45:13 Adding Agents to channels 45:43 Why I use Codex as Lead Agent 47:06 Using Codex, Claude Code and Grok for task 48:52 Adding Muse (Meta Model) using OpenRouter 51:23 iOS app is Free and easy to use 51:50 My management Channel (My #1 use case) ---

Riley Brown

384,688 次观看 • 23 天前

AgentRouter is handing out $125 in FREE API credits for OPUS 4.8 > No card. > GitHub sign-in. > One API key for Opus 4.8 / Opus 4.7 / Sonnet 4.6 / GLM 5.1 The useful part is not “another model gateway.” It is that you can point coding tools and agents at one OpenAI-compatible base URL instead of juggling separate keys for Claude and GLM, and others. What you get: • $125 signup balance • one API key • OpenAI-compatible endpoints • chat, responses, messages, embeddings, images, audio, rerank endpoints listed • claimed support for Cursor, Claude Code, Hermes, and other agent tools The flow is simple: 1. go to AgentRouter (link in comment) 2. sign in or create an account 3. generate an API key in the console 4. copy the base URL 5. paste it into Cursor / Claude Code / your agent runtime 6. run a small test before moving anything serious Caveat: AgentRouter’s own site currently has a notice saying Claude-series service was recently hit by stability issues and large-scale Claude access was suspended. So don’t treat this as “guaranteed free Claude forever.” Treat it as $125 of free routing credits to test which models are live, how the latency feels, and whether the gateway is stable enough for your workflow. Still a very solid save if you build with agents. Most people burn paid API credits just testing configs. This gives you room to test first, then decide if it belongs in your stack.
0:22

AgentRouter is handing out $125 in FREE API credits for OPUS 4.8 > No card. > GitHub sign-in. > One API key for Opus 4.8 / Opus 4.7 / Sonnet 4.6 / GLM 5.1 The useful part is not “another model gateway.” It is that you can point coding tools and agents at one OpenAI-compatible base URL instead of juggling separate keys for Claude and GLM, and others. What you get: • $125 signup balance • one API key • OpenAI-compatible endpoints • chat, responses, messages, embeddings, images, audio, rerank endpoints listed • claimed support for Cursor, Claude Code, Hermes, and other agent tools The flow is simple: 1. go to AgentRouter (link in comment) 2. sign in or create an account 3. generate an API key in the console 4. copy the base URL 5. paste it into Cursor / Claude Code / your agent runtime 6. run a small test before moving anything serious Caveat: AgentRouter’s own site currently has a notice saying Claude-series service was recently hit by stability issues and large-scale Claude access was suspended. So don’t treat this as “guaranteed free Claude forever.” Treat it as $125 of free routing credits to test which models are live, how the latency feels, and whether the gateway is stable enough for your workflow. Still a very solid save if you build with agents. Most people burn paid API credits just testing configs. This gives you room to test first, then decide if it belongs in your stack.

kocer

25,316 次观看 • 2 个月前

NVIDIA SHIPS A 50 POUND AI BOARD FOR DATA CENTERS AND A $249 BOX FOR YOUR DESK. ONE COSTS $200/MONTH TO RENT, THE OTHER COSTS $5 IN ELECTRICITY TO OWN jensen huang held up a 50 pound a100 board on stage with 30,000 components and called it a technology marvel. that same technology now ships in a $249 box smaller than your wallet the jetson orin nano super pulls 7-25 watts and does 67 trillion ai operations per second. llama 3, mistral and deepseek run locally with no api fees and no data leaving your machine most developers pay $2,400 a year across chatgpt, openai api, claude pro and cursor. the jetson costs $314 in year one and $60 a year after. 2 year savings hit $4,431 install ollama with one command, change one line of code to point at localhost, and every tool built for openai works identically. zero rewrites, zero rate limits cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who own the box in 2026 are going to look very far ahead in 2028 bookmark this and read the article below
1:07

NVIDIA SHIPS A 50 POUND AI BOARD FOR DATA CENTERS AND A $249 BOX FOR YOUR DESK. ONE COSTS $200/MONTH TO RENT, THE OTHER COSTS $5 IN ELECTRICITY TO OWN jensen huang held up a 50 pound a100 board on stage with 30,000 components and called it a technology marvel. that same technology now ships in a $249 box smaller than your wallet the jetson orin nano super pulls 7-25 watts and does 67 trillion ai operations per second. llama 3, mistral and deepseek run locally with no api fees and no data leaving your machine most developers pay $2,400 a year across chatgpt, openai api, claude pro and cursor. the jetson costs $314 in year one and $60 a year after. 2 year savings hit $4,431 install ollama with one command, change one line of code to point at localhost, and every tool built for openai works identically. zero rewrites, zero rate limits cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who own the box in 2026 are going to look very far ahead in 2028 bookmark this and read the article below

starmex

24,107 次观看 • 2 个月前

10 free github repos that can replace major SaaS with subscriptions. all free. open-sourced. some are MIT licensed. — 1️⃣ openscreen — replaces screen studio ($29/mo) - a clean macOS/windows/linux screen recorder for polished demos. - blur, cursor highlighting, annotations, export to mp4 or gif at any aspect ratio. - doesn't try to clone every feature, just nails the basics for quick walkthroughs you'd post on X. — 2️⃣ voicebox — replaces elevenlabs ($22/mo) + wisprflow ($15/mo) - local-first AI voice studio. - clone voices from 3 seconds of audio, generate speech across 7 TTS engines in 23 languages, - dictate into any text field with a global hotkey. - nothing leaves your machine. - runs on apple silicon, cuda, rocm. — 3️⃣ openshorts — replaces opus clip ($19/mo) + submagic ($16/mo) - free AI video platform. - clip generator turns long youtube videos into 9:16 shorts with auto-subtitles and face tracking (runs on free gemini + elevenlabs tiers). - also includes AI UGC video generation with actors — that part is pay-per-use via fal. ai (~$0.65-2 per video). docker self-host. — 4️⃣ freellmapi — replaces chatgpt pro + claude pro ($20/mo each) - stacks 14 free AI provider tiers (google, groq, cerebras, openrouter, github models + 9 more) behind one openai-compatible endpoint. ~800M tokens/month. - smart router with failover, sticky sessions, encrypted key storage. ships with a dashboard. — 5️⃣ playwright-mcp — replaces browserbase ($39/mo) + browser use ($25/mo) - microsoft's official MCP server that gives any AI agent full browser control. - uses accessibility trees, not screenshots — deterministic and token-efficient. - works with claude code, cursor, windsurf, codex out of the box. — 6️⃣ vibe-trading — replaces tradingview premium ($60/mo) - natural-language finance research agent. - 7 backtest engines across stocks, crypto, futures, forex. - 75 specialist skills (factor analysis, options strategy, ML strategy). - 29 multi-agent swarm presets. - 21 of 22 MCP tools work with zero API keys. — 7️⃣ CalCom — replaces calendly ($12/mo) + savvycal ($12/mo) - the open-source scheduling infrastructure. - one-on-ones, group events, round-robin, team booking, - payment collection (stripe), routing forms, workflows. - integrates with google/outlook/apple calendar, zoom, meet, teams. - self-host in 10 minutes with docker. 40k stars. — 8️⃣ whisper — replaces otter ($17/mo) - openAI's open-source speech-to-text model. - transcribe audio in 99 languages, translate to english, generate timestamps. - runs locally on cpu or gpu. - the actual model behind most "AI transcription" SaaS tools you're paying for. — 9️⃣ postiz — replaces buffer ($15/mo) - AI-powered social media scheduler. - cross-post to X, linkedin, instagram, tiktok, threads, bluesky, mastodon, youtube, pinterest. - AI captions and hashtags. - analytics dashboard. team workspaces. 31k stars and rising. — 🔟 vaultwarden — replaces 1password ($8/mo) - unofficial bitwarden-compatible server written in rust. - works with every official bitwarden client (mobile, desktop, browser). - unlimited users, unlimited vaults, full enterprise feature set. - runs on a $5 VPS or your home server. — disclaimer: open-source ≠ 1:1 replacement. you'll trade polish for ownership, hand-holding for control, and a credit card for a github version. for builders, prototypers, and indie hackers — that's the whole point. for everyone else, the paid tools still have their place. bookmark this. share with one friend bleeding subscription fees. ~m0h
0:31

10 free github repos that can replace major SaaS with subscriptions. all free. open-sourced. some are MIT licensed. — 1️⃣ openscreen — replaces screen studio ($29/mo) - a clean macOS/windows/linux screen recorder for polished demos. - blur, cursor highlighting, annotations, export to mp4 or gif at any aspect ratio. - doesn't try to clone every feature, just nails the basics for quick walkthroughs you'd post on X. — 2️⃣ voicebox — replaces elevenlabs ($22/mo) + wisprflow ($15/mo) - local-first AI voice studio. - clone voices from 3 seconds of audio, generate speech across 7 TTS engines in 23 languages, - dictate into any text field with a global hotkey. - nothing leaves your machine. - runs on apple silicon, cuda, rocm. — 3️⃣ openshorts — replaces opus clip ($19/mo) + submagic ($16/mo) - free AI video platform. - clip generator turns long youtube videos into 9:16 shorts with auto-subtitles and face tracking (runs on free gemini + elevenlabs tiers). - also includes AI UGC video generation with actors — that part is pay-per-use via fal. ai (~$0.65-2 per video). docker self-host. — 4️⃣ freellmapi — replaces chatgpt pro + claude pro ($20/mo each) - stacks 14 free AI provider tiers (google, groq, cerebras, openrouter, github models + 9 more) behind one openai-compatible endpoint. ~800M tokens/month. - smart router with failover, sticky sessions, encrypted key storage. ships with a dashboard. — 5️⃣ playwright-mcp — replaces browserbase ($39/mo) + browser use ($25/mo) - microsoft's official MCP server that gives any AI agent full browser control. - uses accessibility trees, not screenshots — deterministic and token-efficient. - works with claude code, cursor, windsurf, codex out of the box. — 6️⃣ vibe-trading — replaces tradingview premium ($60/mo) - natural-language finance research agent. - 7 backtest engines across stocks, crypto, futures, forex. - 75 specialist skills (factor analysis, options strategy, ML strategy). - 29 multi-agent swarm presets. - 21 of 22 MCP tools work with zero API keys. — 7️⃣ CalCom — replaces calendly ($12/mo) + savvycal ($12/mo) - the open-source scheduling infrastructure. - one-on-ones, group events, round-robin, team booking, - payment collection (stripe), routing forms, workflows. - integrates with google/outlook/apple calendar, zoom, meet, teams. - self-host in 10 minutes with docker. 40k stars. — 8️⃣ whisper — replaces otter ($17/mo) - openAI's open-source speech-to-text model. - transcribe audio in 99 languages, translate to english, generate timestamps. - runs locally on cpu or gpu. - the actual model behind most "AI transcription" SaaS tools you're paying for. — 9️⃣ postiz — replaces buffer ($15/mo) - AI-powered social media scheduler. - cross-post to X, linkedin, instagram, tiktok, threads, bluesky, mastodon, youtube, pinterest. - AI captions and hashtags. - analytics dashboard. team workspaces. 31k stars and rising. — 🔟 vaultwarden — replaces 1password ($8/mo) - unofficial bitwarden-compatible server written in rust. - works with every official bitwarden client (mobile, desktop, browser). - unlimited users, unlimited vaults, full enterprise feature set. - runs on a $5 VPS or your home server. — disclaimer: open-source ≠ 1:1 replacement. you'll trade polish for ownership, hand-holding for control, and a credit card for a github version. for builders, prototypers, and indie hackers — that's the whole point. for everyone else, the paid tools still have their place. bookmark this. share with one friend bleeding subscription fees. ~m0h

m0h

247,857 次观看 • 3 个月前

8 rules to improve your AI coding agent. All of these rules work with Claude Code, Cursor, VS Code, and with most programming languages. Automating these rules will 10x the code quality and security produced by your AI coding agents. 1. Dependency checks - Prevent your agent from suggesting insecure libraries based on outdated training data. 2. Secret exposure - Auto-fix the use of hardcoded credentials introduced by your coding agent. 3. File and function size - Automatically refactor any files or functions that exceed a reasonable length. 4. Complexity and parameter limits - Simplify overly complex code written by the agent. 5. SQL Injection - Auto-fix all database interactions with unsanitized user input. 6. Unused variables and imports - Detect and remove dead code. 7. Detect invisible unicode characters in AI rules files - Remove zero-width spaces, direction overrides, and other invisible characters that can hide malicious behavior. 8. Insecure OpenAI API usage - Enforce use of secure OpenAI endpoints, proper authentication, and context isolation Here is how you can automate this: Install the Codacy extension. This will give you access to a CLI for local scanning and an MCP server for agent communication. From here on out, every time you need to generate some code: 1. Your agent will write the code 2. It will then call Codacy's CLI to check it 3. It will find any issues in real time 4. Your coding agent will fix the issues 5. When the code passes all checks, you are done Level of effort on your side: literally zero! Code quality and security because of this: 100x better! Here is the link to download the extension for your IDE: Thanks to the Codacy team for collaborating with me on this post.
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8 rules to improve your AI coding agent. All of these rules work with Claude Code, Cursor, VS Code, and with most programming languages. Automating these rules will 10x the code quality and security produced by your AI coding agents. 1. Dependency checks - Prevent your agent from suggesting insecure libraries based on outdated training data. 2. Secret exposure - Auto-fix the use of hardcoded credentials introduced by your coding agent. 3. File and function size - Automatically refactor any files or functions that exceed a reasonable length. 4. Complexity and parameter limits - Simplify overly complex code written by the agent. 5. SQL Injection - Auto-fix all database interactions with unsanitized user input. 6. Unused variables and imports - Detect and remove dead code. 7. Detect invisible unicode characters in AI rules files - Remove zero-width spaces, direction overrides, and other invisible characters that can hide malicious behavior. 8. Insecure OpenAI API usage - Enforce use of secure OpenAI endpoints, proper authentication, and context isolation Here is how you can automate this: Install the Codacy extension. This will give you access to a CLI for local scanning and an MCP server for agent communication. From here on out, every time you need to generate some code: 1. Your agent will write the code 2. It will then call Codacy's CLI to check it 3. It will find any issues in real time 4. Your coding agent will fix the issues 5. When the code passes all checks, you are done Level of effort on your side: literally zero! Code quality and security because of this: 100x better! Here is the link to download the extension for your IDE: Thanks to the Codacy team for collaborating with me on this post.

Santiago

49,331 次观看 • 10 个月前