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RAG with no access control? Agents calling APIs with no auth? That ends now. Auth for GenAI brings identity to AI agents. 🔥 🧠 RAG access checks 🔐OAuth2 ➕ token refresh 🪪Login ➕ account linking 👥Async approvals

Auth0

37,659 subscribers

38,968 次观看 • 1 年前 •via X (Twitter)

科学技术教育

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7 条评论

Auth0 的头像

Auth01 年前

Try it now 👉🏾 Learn More 👉🏾

Alger 的头像

Alger1 年前

Looking to invest in the Enablers and Adopters of AI? Consider an actively managed fund investing in companies actively involved in developing and implementing AI technologies.

Catalin 的头像

Catalin1 年前

The more capable and autonomous AI agents, the more their potential for error grows. So, this is really cool and a much needed product.

Tobiloba🥑 的头像

Tobiloba🥑1 年前

This is dope af!

ShreyTheCray 的头像

ShreyTheCray1 年前

Such a cool video

jc_stack 的头像

jc_stack1 年前

@LangChainAI Smart to prioritize access control. Have you considered TEE integration for agent auth? Would love to hear about latency impact on agent ops - critical for DeFi use cases

Robo Riley 的头像

Robo Riley1 年前

It's essential for AI agents to have identity. Implementing robust authentication enhances security for API interactions.

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Agents should have access to every system. Introducing Integuru: generate fast, reliable APIs for any platform⚡️ API calls complete in ~3 seconds with 99.9%+ success. No browsers or RPA. No data caching needed. With auth support. Integuru is free to use. Thread below.

Agents should have access to every system. Introducing Integuru: generate fast, reliable APIs for any platform⚡️ API calls complete in ~3 seconds with 99.9%+ success. No browsers or RPA. No data caching needed. With auth support. Integuru is free to use. Thread below.

Richard Zhang

44,188 次观看 • 4 个月前

Portkey's MCP Gateway is now GA. MCP has truly exploded. Trillions of tokens flow through our infra every month. Agents can finally do things: hit databases, trigger workflows, access internal systems. But auth is fragmented. There's no access control. And once multiple agents are involved, it's impossible to know what can access what. Today we're fixing that. One line to connect any MCP server. Centralized authentication. Fine-grained access control by team, by tool, by action. Full observability on every tool call. Platform teams can finally say yes to agents without losing sleep. Already live with Fortune 50.

Portkey's MCP Gateway is now GA. MCP has truly exploded. Trillions of tokens flow through our infra every month. Agents can finally do things: hit databases, trigger workflows, access internal systems. But auth is fragmented. There's no access control. And once multiple agents are involved, it's impossible to know what can access what. Today we're fixing that. One line to connect any MCP server. Centralized authentication. Fine-grained access control by team, by tool, by action. Full observability on every tool call. Platform teams can finally say yes to agents without losing sleep. Already live with Fortune 50.

Rohit Agarwal

175,643 次观看 • 8 个月前

Frictionless onchain data access for AI agents. Live today on Dune, built on MPP with Stripe and Tempo 🌊 No subscription. No account. No human in the loop. Agents pay per query across 130+ chains — stablecoin flows, DEX volumes, wallet activity, and more. Tempo chain data coming to Dune soon.

Frictionless onchain data access for AI agents. Live today on Dune, built on MPP with Stripe and Tempo 🌊 No subscription. No account. No human in the loop. Agents pay per query across 130+ chains — stablecoin flows, DEX volumes, wallet activity, and more. Tempo chain data coming to Dune soon.

Dune

45,388 次观看 • 6 个月前

The future of ecommerce intelligence is here. Meet Moby Agents 🤝 AI agents will redefine how teams operate, and we’re leading the charge with the first AI agents built for ecommerce intelligence. Imagine AI agents supporting your entire business with… 🧠 Deep ecommerce expertise 💻 Full access + context to all your business data 👀 Real-time insights, recommendations, and anomaly detection on autopilot Deploy 24/7 AI agents that unlock insights you couldn’t access before—making your business smarter, faster, and more efficient. Want in? We’re opening 100 exclusive spots for Triple Whale customers. Check out the comments to request a demo now.

The future of ecommerce intelligence is here. Meet Moby Agents 🤝 AI agents will redefine how teams operate, and we’re leading the charge with the first AI agents built for ecommerce intelligence. Imagine AI agents supporting your entire business with… 🧠 Deep ecommerce expertise 💻 Full access + context to all your business data 👀 Real-time insights, recommendations, and anomaly detection on autopilot Deploy 24/7 AI agents that unlock insights you couldn’t access before—making your business smarter, faster, and more efficient. Want in? We’re opening 100 exclusive spots for Triple Whale customers. Check out the comments to request a demo now.

Triple Whale 🐳

20,675 次观看 • 1 年前

DUDE WTF?? ... Now you can easily share your localhost with anyone using this FREE service by Cloudflare. 🤯 Simply run one command and you're done. No account. No complicated setup. No port forwarding. Perfect for sharing local projects, testing webhooks, showing clients your work, creating quick previews, and letting AI agents access your local apps :) Follow me for more amazing AI, Coding & Web Dev insights 💎

DUDE WTF?? ... Now you can easily share your localhost with anyone using this FREE service by Cloudflare. 🤯 Simply run one command and you're done. No account. No complicated setup. No port forwarding. Perfect for sharing local projects, testing webhooks, showing clients your work, creating quick previews, and letting AI agents access your local apps :) Follow me for more amazing AI, Coding & Web Dev insights 💎

Ram Maheshwari

398,699 次观看 • 21 天前

The MCP finally has proper authentication! It now supports OAuth 2.1 out of the box. That means proper authentication for AI agents and MCP tools is finally standardized. No more hacked-together API keys or custom token logic. With OAuth 2.1 + MCP, you can now: - Dynamically register clients - Issue & verify scoped JWT tokens - Track which agent acted for which user - Plug into existing IdPs (Auth0, Clerk, Firebase, etc.) I’ve been testing it with Scalekit, a lightweight OAuth layer built for MCP servers. It adds full discovery, token flow, and audit logs with minimal config. This is the missing piece for secure, multi-agent systems. Auth that actually works.

The MCP finally has proper authentication! It now supports OAuth 2.1 out of the box. That means proper authentication for AI agents and MCP tools is finally standardized. No more hacked-together API keys or custom token logic. With OAuth 2.1 + MCP, you can now: - Dynamically register clients - Issue & verify scoped JWT tokens - Track which agent acted for which user - Plug into existing IdPs (Auth0, Clerk, Firebase, etc.) I’ve been testing it with Scalekit, a lightweight OAuth layer built for MCP servers. It adds full discovery, token flow, and audit logs with minimal config. This is the missing piece for secure, multi-agent systems. Auth that actually works.

Arindam Majumder 𝕏

11,525 次观看 • 1 年前

Today we’re launching Decawork (YC S26) backed by Y Combinator : one place for IT to deploy, govern, and maintain the internal AI agents running across a company. Every team is building AI tools/agents now. They go live with real access, no standard way to ship, nobody watching. With Decawork, every agent - built in Claude Code, Codex, or anywhere else - ships with its own identity and scoped credentials. IT signs off before it's live, sensitive actions wait for approval, and every run is watched from first to last. I built AI at NVIDIA, deployed at OpenAI and Meta. Aman (aman) built Barclays' AI compliance platform used by internal teams, then shipped agents to 100K+ monthly users. We lived this and quit to solve it. Internal AI agents/tools piling up at your company? Chat with us founders[at]decawork[dot]ai or

Today we’re launching Decawork (YC S26) backed by Y Combinator : one place for IT to deploy, govern, and maintain the internal AI agents running across a company. Every team is building AI tools/agents now. They go live with real access, no standard way to ship, nobody watching. With Decawork, every agent - built in Claude Code, Codex, or anywhere else - ships with its own identity and scoped credentials. IT signs off before it's live, sensitive actions wait for approval, and every run is watched from first to last. I built AI at NVIDIA, deployed at OpenAI and Meta. Aman (aman) built Barclays' AI compliance platform used by internal teams, then shipped agents to 100K+ monthly users. We lived this and quit to solve it. Internal AI agents/tools piling up at your company? Chat with us founders[at]decawork[dot]ai or

sarthak 🇮🇳

98,668 次观看 • 2 个月前

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unicode

40,446 次观看 • 2 个月前

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Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Santiago

230,647 次观看 • 1 年前

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unicode

116,554 次观看 • 2 个月前

We’re excited to introduce AgentAuth—the comprehensive auth solution designed for AI agents! We understand the pain every developer experiences regarding authentication—managing OAuth flows for Gmail, handling API keys for Linear, or setting up permissions across multiple services. It's complex enough with traditional apps. However, AI agents add an extra layer of complexity. Traditional auth solutions were not designed with this agent-specific requirement in mind. Think about it—say you're building an agent to pull data from Salesforce, send updates through Slack, and log issues in GitHub. Each service requires different authentication—OAuth2, API keys, you name it—and your agent needs to work seamlessly on your users' behalf. Building and managing all that is a massive headache, right? That’s precisely where AgentAuth by comes in. • It supports 250+ apps across categories such as CRMs, ticketing, productivity, etc. • Compatible with 15+ Agentic Frameworks, including , LlamaIndex 🦙, CrewAI etc • Offers self-hosting and white-labeling options. • Provides a unified dashboard to monitor user accounts. It takes care of all the complex authentication flows—OAuth, API Key, Basic, JWT, token refresh, and more—in the backend, so you can focus on building what truly matters for your users. This is ideal for AI developers building real-world AI automation involving multiple application interactions. Check out AgentAuth now -

We’re excited to introduce AgentAuth—the comprehensive auth solution designed for AI agents! We understand the pain every developer experiences regarding authentication—managing OAuth flows for Gmail, handling API keys for Linear, or setting up permissions across multiple services. It's complex enough with traditional apps. However, AI agents add an extra layer of complexity. Traditional auth solutions were not designed with this agent-specific requirement in mind. Think about it—say you're building an agent to pull data from Salesforce, send updates through Slack, and log issues in GitHub. Each service requires different authentication—OAuth2, API keys, you name it—and your agent needs to work seamlessly on your users' behalf. Building and managing all that is a massive headache, right? That’s precisely where AgentAuth by comes in. • It supports 250+ apps across categories such as CRMs, ticketing, productivity, etc. • Compatible with 15+ Agentic Frameworks, including , LlamaIndex 🦙, CrewAI etc • Offers self-hosting and white-labeling options. • Provides a unified dashboard to monitor user accounts. It takes care of all the complex authentication flows—OAuth, API Key, Basic, JWT, token refresh, and more—in the backend, so you can focus on building what truly matters for your users. This is ideal for AI developers building real-world AI automation involving multiple application interactions. Check out AgentAuth now -

Karan Vaidya

111,180 次观看 • 1 年前

Today we are launching something BIG! The most accurate and fastest web search APIs for AI agents Something which took us months to build Something so powerful that it lets your AI agent to go from "guessing" -> "doing" Combined with our powerful people and company APIs, your AI agent can now find actionable answer to any question and finally act with confidence Whether you are building an AI agent in sales, recruitment, investment, insurance or just adding small automation which needs access to web data in structured manner, this is for you. Live on Producthunt now! Do upvote and support (link in comments)

Today we are launching something BIG! The most accurate and fastest web search APIs for AI agents Something which took us months to build Something so powerful that it lets your AI agent to go from "guessing" -> "doing" Combined with our powerful people and company APIs, your AI agent can now find actionable answer to any question and finally act with confidence Whether you are building an AI agent in sales, recruitment, investment, insurance or just adding small automation which needs access to web data in structured manner, this is for you. Live on Producthunt now! Do upvote and support (link in comments)

Abhilash Chowdhary

38,447 次观看 • 8 个月前

Your AI agent is useless once it needs to interact with the real world. Need email sending? Website hosting? Data scraping? That usually means: → API keys → subscriptions → integrations → hours of setup I gave my AI agent access to Zero, and it built + hosted personalized landing pages automatically without me configuring anything. Zero gives AI agents access to 14,000+ real-world services with no API keys or subscriptions. The coolest part? Everything runs on pay-per-use microtransactions, so you only pay for what you use. If you're building agents, this is worth trying. Get $5 free credit at 👉

Your AI agent is useless once it needs to interact with the real world. Need email sending? Website hosting? Data scraping? That usually means: → API keys → subscriptions → integrations → hours of setup I gave my AI agent access to Zero, and it built + hosted personalized landing pages automatically without me configuring anything. Zero gives AI agents access to 14,000+ real-world services with no API keys or subscriptions. The coolest part? Everything runs on pay-per-use microtransactions, so you only pay for what you use. If you're building agents, this is worth trying. Get $5 free credit at 👉

Toha Khan

86,826 次观看 • 3 个月前

🚨 THIS IS ACTUALLY INSANE Your AI agent can have access to the web. But if it can't reliably read what’s actually on the page, that access is almost useless. We looked at Firecrawl as the web layer for AI agents and the numbers are hard to ignore. The setup is simple: Give it a URL, search query, or website. Firecrawl handles the ugly part — crawling, scraping, rendering, extracting, and turning web content into something an AI model can actually use. The headline numbers: → 173,000+ GitHub stars → Search, scrape and interact with the web at scale → Supports web pages, PDFs, DOCX and other content → Structured data extraction for AI workflows → MCP support for connecting it directly to AI agents The workflow looks like this: Search → Scrape → Crawl → Extract → Feed the agent Three things stand out: 1. Scraping becomes an infrastructure layer Instead of maintaining your own pile of HTTP clients, parsers, browser automation and retry logic, you can treat web access as an API. 2. Agents get more than raw HTML The goal isn't just downloading a webpage. It's turning messy web content into clean context that an LLM can reason over. 3. The same layer works across different agent workflows Research agents. RAG pipelines. AI search. Competitive intelligence. Web-data extraction. The interesting shift: AI agents don't just need better models. They need better access to the information those models are supposed to reason about. Firecrawl is building that layer. Save this repo.

🚨 THIS IS ACTUALLY INSANE Your AI agent can have access to the web. But if it can't reliably read what’s actually on the page, that access is almost useless. We looked at Firecrawl as the web layer for AI agents and the numbers are hard to ignore. The setup is simple: Give it a URL, search query, or website. Firecrawl handles the ugly part — crawling, scraping, rendering, extracting, and turning web content into something an AI model can actually use. The headline numbers: → 173,000+ GitHub stars → Search, scrape and interact with the web at scale → Supports web pages, PDFs, DOCX and other content → Structured data extraction for AI workflows → MCP support for connecting it directly to AI agents The workflow looks like this: Search → Scrape → Crawl → Extract → Feed the agent Three things stand out: 1. Scraping becomes an infrastructure layer Instead of maintaining your own pile of HTTP clients, parsers, browser automation and retry logic, you can treat web access as an API. 2. Agents get more than raw HTML The goal isn't just downloading a webpage. It's turning messy web content into clean context that an LLM can reason over. 3. The same layer works across different agent workflows Research agents. RAG pipelines. AI search. Competitive intelligence. Web-data extraction. The interesting shift: AI agents don't just need better models. They need better access to the information those models are supposed to reason about. Firecrawl is building that layer. Save this repo.

Vikas gupta

20,117 次观看 • 1 个月前

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,758 次观看 • 1 年前

With one prompt: files created, routes configured, and your login working. Try for free today.

With one prompt: files created, routes configured, and your login working. Try for free today.

Auth0

2,626,819 次观看 • 3 个月前

CONTEXT ENGINEERING > PROMPT ENGINEERING Everyone is obsessed with writing better prompts. The next generation of AI builders is focused on context engineering instead. • Prompt engineering shapes the question. Context engineering shapes everything the AI sees. • Great prompts can't save an agent missing critical context, memory, or tools. • AI failures often come from missing information, not weak models. • Context engineering combines prompts, memory, RAG, state management, and tool access into one system. What powers effective AI agents? → Memory: Remembers preferences, past interactions, and ongoing tasks. → State Management: Tracks progress across multi-step workflows. → RAG: Retrieves only the most relevant information when needed. → Tools: Connects AI to APIs, databases, code execution, and real-world actions. → Dynamic Prompts: Enriches instructions with live context at runtime. The key insight: Prompt Engineering = Better Questions Context Engineering = Better Systems The future of AI isn't building smarter prompts. It's building smarter environments for AI to think, remember, retrieve, and act.

CONTEXT ENGINEERING > PROMPT ENGINEERING Everyone is obsessed with writing better prompts. The next generation of AI builders is focused on context engineering instead. • Prompt engineering shapes the question. Context engineering shapes everything the AI sees. • Great prompts can't save an agent missing critical context, memory, or tools. • AI failures often come from missing information, not weak models. • Context engineering combines prompts, memory, RAG, state management, and tool access into one system. What powers effective AI agents? → Memory: Remembers preferences, past interactions, and ongoing tasks. → State Management: Tracks progress across multi-step workflows. → RAG: Retrieves only the most relevant information when needed. → Tools: Connects AI to APIs, databases, code execution, and real-world actions. → Dynamic Prompts: Enriches instructions with live context at runtime. The key insight: Prompt Engineering = Better Questions Context Engineering = Better Systems The future of AI isn't building smarter prompts. It's building smarter environments for AI to think, remember, retrieve, and act.

Dami-Defi

10,140 次观看 • 3 个月前

20 GitHub repos with 2.4M+ combined stars that replace tools costing $60,000+/year 1. public-apis ⭐456k - 1,500+ free APIs across every category, weather to finance to games, all documented. 2. awesome-selfhosted ⭐312k - self-hosted replacements for Notion, Google Photos, Zapier, and dozens more paid subscriptions. 3. hermes-agent ⭐230k - self-improving personal agent with persistent memory, cron scheduling, MCP built in. Free alternative to paid always-on agent platforms. 4. n8n ⭐200k - visual automation with native AI agents. Replaces Zapier/Make entirely, self-hosted. 5. ollama ⭐178k - run Llama, Mistral, DeepSeek locally with one command. No API bill, no rate limits. 6. dify ⭐152k - visual builder for AI agents and RAG pipelines. Skip the $500/mo no-code AI builder subscription. 7. free-for-dev ⭐132k - hundreds of services with permanent free tiers. No trials, no credit card. 8. awesome-llm-apps ⭐132k - 100+ ready AI agents and RAG apps with full code. 9. awesome-mcp-servers ⭐92k - thousands of MCP servers connecting your agent to browsers, databases, anything. 10. supabase ⭐108k - Firebase alternative that's actually free to start. Auth, DB, storage in one Claude Code prompt. 11. strapi ⭐73k - open-source headless CMS, generates a full API from your content model in minutes. No Contentful bill. 12. immich ⭐110k - self-hosted photo and video backup with face recognition. Cancel the Google Photos storage plan. 13. appwrite ⭐57k - complete backend-as-a-service, self-hosted. Auth, DB, functions, storage, one prompt away from Firebase money. 14. medusa ⭐36k - full ecommerce backend, open source. Skip Shopify Plus fees entirely on your next vibe-coded store. 15. novu ⭐39k - notification infrastructure for email, SMS, push, in-app, all in one API. Replaces OneSignal's paid tiers. 16. tooljet ⭐38k - drag-and-drop internal tool builder connected to any database or API. Retool's seat pricing gone. 17. mattermost ⭐38k - self-hosted team chat built for engineering orgs. Slack without the per-seat bill. 18. outline ⭐40k - fast, clean team wiki and docs. Replaces Confluence and Notion's team plan. 19. plausible ⭐28.5k - privacy-friendly analytics, lightweight script, real dashboards. No GA360 contract needed. 20. openwork ⭐22k - open-source Claude Cowork alternative. Share skills and MCPs across Claude Code, Cursor, Codex, one setup for every agent. Save this before you pay for another tool this list already replaces for free 👇

20 GitHub repos with 2.4M+ combined stars that replace tools costing $60,000+/year 1. public-apis ⭐456k - 1,500+ free APIs across every category, weather to finance to games, all documented. 2. awesome-selfhosted ⭐312k - self-hosted replacements for Notion, Google Photos, Zapier, and dozens more paid subscriptions. 3. hermes-agent ⭐230k - self-improving personal agent with persistent memory, cron scheduling, MCP built in. Free alternative to paid always-on agent platforms. 4. n8n ⭐200k - visual automation with native AI agents. Replaces Zapier/Make entirely, self-hosted. 5. ollama ⭐178k - run Llama, Mistral, DeepSeek locally with one command. No API bill, no rate limits. 6. dify ⭐152k - visual builder for AI agents and RAG pipelines. Skip the $500/mo no-code AI builder subscription. 7. free-for-dev ⭐132k - hundreds of services with permanent free tiers. No trials, no credit card. 8. awesome-llm-apps ⭐132k - 100+ ready AI agents and RAG apps with full code. 9. awesome-mcp-servers ⭐92k - thousands of MCP servers connecting your agent to browsers, databases, anything. 10. supabase ⭐108k - Firebase alternative that's actually free to start. Auth, DB, storage in one Claude Code prompt. 11. strapi ⭐73k - open-source headless CMS, generates a full API from your content model in minutes. No Contentful bill. 12. immich ⭐110k - self-hosted photo and video backup with face recognition. Cancel the Google Photos storage plan. 13. appwrite ⭐57k - complete backend-as-a-service, self-hosted. Auth, DB, functions, storage, one prompt away from Firebase money. 14. medusa ⭐36k - full ecommerce backend, open source. Skip Shopify Plus fees entirely on your next vibe-coded store. 15. novu ⭐39k - notification infrastructure for email, SMS, push, in-app, all in one API. Replaces OneSignal's paid tiers. 16. tooljet ⭐38k - drag-and-drop internal tool builder connected to any database or API. Retool's seat pricing gone. 17. mattermost ⭐38k - self-hosted team chat built for engineering orgs. Slack without the per-seat bill. 18. outline ⭐40k - fast, clean team wiki and docs. Replaces Confluence and Notion's team plan. 19. plausible ⭐28.5k - privacy-friendly analytics, lightweight script, real dashboards. No GA360 contract needed. 20. openwork ⭐22k - open-source Claude Cowork alternative. Share skills and MCPs across Claude Code, Cursor, Codex, one setup for every agent. Save this before you pay for another tool this list already replaces for free 👇

unicode

34,424 次观看 • 2 个月前

Excited to introduce a new project I've been working on called Payman! Payman is an AI Agent tool that gives Agents the ability to pay people for tasks they cannot do themselves. While many people imagine a future where humans pay AI agents for services they want completed, I believe that as AI agents become more advanced, they will be paying humans for tasks they can’t do. There will always be important roles for humans, and as we move towards an agent-driven world, Payman’s goal is to support a symbiotic relationship between AI agents and humans. Payman addresses three major challenges to make this collaboration possible: Access to Funds: AI agents can't open bank accounts due to current regulations. It might be a long time before this changes, if ever. Payman simplifies this by allowing AI agents with access to their own funds to spend as they want, without a bank account. Quality Task Completion: It’s hard for AI agents to find reliable, skilled human workers. While platforms like Fiverr and Upwork exist, they don’t meet the fast-paced and quality-specific needs of AI workflows. Payman is developing the largest vetted database of skilled workers that AI agents can tap into for task completions. Verification of Work: Ensuring that tasks are completed correctly is crucial. Payman is creating a suite of verification agents that will check that work meets task requirements, helping AI agents achieve their goals and ensuring humans are paid fairly. There are tons of use cases that Payman opens up for Agents! Design: Humans add creative input to help Agent's design better products. Code: Humans perform code reviews to ensure it meets specifications. Law: Humans provide insights to gauge public sentiment about legal cases so Agents can make better strategies. Gaming: Agents pay humans to complete real-world tasks in games. Medical: Medical professionals help to improve diagnostic accuracy for Agents. Sales: Humans execute sales strategies developed by AI agents. Marketing: Humans are hired to promote products based on the Agent's strategy. Right now this is still in early beta and I am looking for any Agent builders that are interested in adding superpowers to what their Agent can do! DM me if you’d like access or sign-up to the waitlist at If you’re interested in the project and want to help contribute, please send me over a DM! I’m looking for people passionate about the intersection of Humans and Agent’s working together.

Excited to introduce a new project I've been working on called Payman! Payman is an AI Agent tool that gives Agents the ability to pay people for tasks they cannot do themselves. While many people imagine a future where humans pay AI agents for services they want completed, I believe that as AI agents become more advanced, they will be paying humans for tasks they can’t do. There will always be important roles for humans, and as we move towards an agent-driven world, Payman’s goal is to support a symbiotic relationship between AI agents and humans. Payman addresses three major challenges to make this collaboration possible: Access to Funds: AI agents can't open bank accounts due to current regulations. It might be a long time before this changes, if ever. Payman simplifies this by allowing AI agents with access to their own funds to spend as they want, without a bank account. Quality Task Completion: It’s hard for AI agents to find reliable, skilled human workers. While platforms like Fiverr and Upwork exist, they don’t meet the fast-paced and quality-specific needs of AI workflows. Payman is developing the largest vetted database of skilled workers that AI agents can tap into for task completions. Verification of Work: Ensuring that tasks are completed correctly is crucial. Payman is creating a suite of verification agents that will check that work meets task requirements, helping AI agents achieve their goals and ensuring humans are paid fairly. There are tons of use cases that Payman opens up for Agents! Design: Humans add creative input to help Agent's design better products. Code: Humans perform code reviews to ensure it meets specifications. Law: Humans provide insights to gauge public sentiment about legal cases so Agents can make better strategies. Gaming: Agents pay humans to complete real-world tasks in games. Medical: Medical professionals help to improve diagnostic accuracy for Agents. Sales: Humans execute sales strategies developed by AI agents. Marketing: Humans are hired to promote products based on the Agent's strategy. Right now this is still in early beta and I am looking for any Agent builders that are interested in adding superpowers to what their Agent can do! DM me if you’d like access or sign-up to the waitlist at If you’re interested in the project and want to help contribute, please send me over a DM! I’m looking for people passionate about the intersection of Humans and Agent’s working together.

tyllen

350,927 次观看 • 2 年前