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Cline has shipped Cline SDK, an open-source agent runtime that now powers the CLI, VS Code, JetBrains, and Kanban, and is available for any team to build on. The whole Cline product line is being migrated onto it. > Cline CLI scores 74.2% on Terminal Bench 2.0 with claude-opus-4.7,... show more

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Cline for CLI is here 🚀 `npm i -g cline` open source and scriptable for you to build ontop of -> Slack bots, GitHub actions, or even have VSCode Cline use it as subagents. This is the first step to bringing Cline everywhere you work.

Cline for CLI is here 🚀 `npm i -g cline` open source and scriptable for you to build ontop of -> Slack bots, GitHub actions, or even have VSCode Cline use it as subagents. This is the first step to bringing Cline everywhere you work.

Saoud Rizwan

32,391 görüntüleme • 11 ay önce

Over the past 6 months, we've rearchitected Cline's agentic loop into a standalone "cline core" gRPC service that runs independently of any editor. This enabled us to decouple from VS code and build - JetBrains (released in GA this week) - CLI built in Go (releasing soon) - Secret project that may be announced soon The CLI is our newest product and will ship without a TUI. Our focus is to release a true primitive. something close to the metal that pipes cleanly into RL environments, CI/CD systems, scripts, and automation workflows. Any "presentation layer" mentioned above can connect to the same running cline core - maintaining full feature parity (e.g. checkpoints, settings, api configurations), context, and conversation state. There's an SQLite-based instance and file/directory lock registry that prevents port conflicts and coordinates graceful shutdowns between paired processes - so you can start up thousands of cline instances in parallel with no conflicts or dangling processes. What's remarkable is that this cline core architecture opens Cline to any interface imaginable: mobile apps, web dashboards, custom tools - all powered by the same intelligent core that understands your codebase.

Over the past 6 months, we've rearchitected Cline's agentic loop into a standalone "cline core" gRPC service that runs independently of any editor. This enabled us to decouple from VS code and build - JetBrains (released in GA this week) - CLI built in Go (releasing soon) - Secret project that may be announced soon The CLI is our newest product and will ship without a TUI. Our focus is to release a true primitive. something close to the metal that pipes cleanly into RL environments, CI/CD systems, scripts, and automation workflows. Any "presentation layer" mentioned above can connect to the same running cline core - maintaining full feature parity (e.g. checkpoints, settings, api configurations), context, and conversation state. There's an SQLite-based instance and file/directory lock registry that prevents port conflicts and coordinates graceful shutdowns between paired processes - so you can start up thousands of cline instances in parallel with no conflicts or dangling processes. What's remarkable is that this cline core architecture opens Cline to any interface imaginable: mobile apps, web dashboards, custom tools - all powered by the same intelligent core that understands your codebase.

pash

59,960 görüntüleme • 1 yıl önce

🚨 This tool just made every AI coding plugin look outdated. Cline CLI 2.0 is a completely rebuilt, open-source AI coding agent that runs entirely in the terminal. Model-agnostic, editor-agnostic, Apache 2.0 licensed, and trusted by over 5 million developers. Same core engine as the VS Code extension rebuilt for how serious development actually happens. The new interactive UI feels genuinely native. Redesigned navigation, real-time agent reasoning, model switching mid-session, all without leaving the terminal. Parallel agents let multiple Cline instances run across tmux panes simultaneously, each with fully isolated state, working different tasks on different branches without conflicts. Headless mode with the `-y` flag plugs Cline directly into CI/CD pipelines, pipe a git diff in, get a code review out. And the `--acp` flag connects to Zed, Neovim, Emacs, and any ACP-compatible editor, so there's no forced editor choice. At launch, Minimax M2.5 and Kimi K2.5 are completely free. No API key. No credit card. Zero barrier to try it. `npm install -g cline` Docs → GitHub → The future of AI coding isn't a plugin. It's infrastructure.

🚨 This tool just made every AI coding plugin look outdated. Cline CLI 2.0 is a completely rebuilt, open-source AI coding agent that runs entirely in the terminal. Model-agnostic, editor-agnostic, Apache 2.0 licensed, and trusted by over 5 million developers. Same core engine as the VS Code extension rebuilt for how serious development actually happens. The new interactive UI feels genuinely native. Redesigned navigation, real-time agent reasoning, model switching mid-session, all without leaving the terminal. Parallel agents let multiple Cline instances run across tmux panes simultaneously, each with fully isolated state, working different tasks on different branches without conflicts. Headless mode with the `-y` flag plugs Cline directly into CI/CD pipelines, pipe a git diff in, get a code review out. And the `--acp` flag connects to Zed, Neovim, Emacs, and any ACP-compatible editor, so there's no forced editor choice. At launch, Minimax M2.5 and Kimi K2.5 are completely free. No API key. No credit card. Zero barrier to try it. `npm install -g cline` Docs → GitHub → The future of AI coding isn't a plugin. It's infrastructure.

AI Frontliner

60,126 görüntüleme • 7 ay önce

Claude Managed Agents 🤝 AG-UI Anthropic just shipped a full AG-UI integration, so you can bring your Managed Agent to any AG-UI frontend with: - Generative UI - Streaming - Tool calls - Stateful sessions Includes React & React Native, Next.js, Angular as well as Slack, Teams and more via the Channels SDK. All open source. Great collaborating with CJ Avilla from Anthropic on this! Check the blog for repos:

Claude Managed Agents 🤝 AG-UI Anthropic just shipped a full AG-UI integration, so you can bring your Managed Agent to any AG-UI frontend with: - Generative UI - Streaming - Tool calls - Stateful sessions Includes React & React Native, Next.js, Angular as well as Slack, Teams and more via the Channels SDK. All open source. Great collaborating with CJ Avilla from Anthropic on this! Check the blog for repos:

Atai Barkai

34,372 görüntüleme • 1 ay önce

So Alibaba has just released a coding plan with all the best open source models You’ve access to Qwen 3.5-Plus, Kimi K2.5, MiniMax M2.5, GLM-5, etc. And you can plug it to: - Claude Code (as I did) - OpenClaw - Codex - Cline… While being waaay cheaper than the paid plan of Codex, Claude & Cie. More below

So Alibaba has just released a coding plan with all the best open source models You’ve access to Qwen 3.5-Plus, Kimi K2.5, MiniMax M2.5, GLM-5, etc. And you can plug it to: - Claude Code (as I did) - OpenClaw - Codex - Cline… While being waaay cheaper than the paid plan of Codex, Claude & Cie. More below

Paul Couvert

88,449 görüntüleme • 7 ay önce

5 GitHub repos with ⭐50K+ combined stars that show how far people are pushing Claude Code beyond a single coding agent 1) instructkr/claude-code 2.3K⭐ -> a research snapshot of Claude Code’s source with the internals exposed for inspection. [ ] 2) codeaashu/claude-code 3.2K⭐ -> another reconstructed Claude Code codebase built for studying how the agent works under the hood, including tools, prompts, MCP. [ ] 3) Donchitos/Claude-Code-Game-Studios 20K+⭐ -> turns one Claude Code session into a game development studio with 49 specialized agents, 73 skills, 12 hooks, 11 rules and 41 templates. [ ] 4) VoltAgent/awesome-claude-code-subagents 24K+⭐ -> 154 specialized Claude Code subagents split across 10 categories. [ ] 5) tanbiralam/claude-code 2.2K⭐ -> a research-oriented Claude Code source reconstruction for inspecting the terminal agent architecture, plugins, tools and internal implementation. [ ] Save these if you want to understand what people are actually building around Claude Code instead of just using the default CLI.

5 GitHub repos with ⭐50K+ combined stars that show how far people are pushing Claude Code beyond a single coding agent 1) instructkr/claude-code 2.3K⭐ -> a research snapshot of Claude Code’s source with the internals exposed for inspection. [ ] 2) codeaashu/claude-code 3.2K⭐ -> another reconstructed Claude Code codebase built for studying how the agent works under the hood, including tools, prompts, MCP. [ ] 3) Donchitos/Claude-Code-Game-Studios 20K+⭐ -> turns one Claude Code session into a game development studio with 49 specialized agents, 73 skills, 12 hooks, 11 rules and 41 templates. [ ] 4) VoltAgent/awesome-claude-code-subagents 24K+⭐ -> 154 specialized Claude Code subagents split across 10 categories. [ ] 5) tanbiralam/claude-code 2.2K⭐ -> a research-oriented Claude Code source reconstruction for inspecting the terminal agent architecture, plugins, tools and internal implementation. [ ] Save these if you want to understand what people are actually building around Claude Code instead of just using the default CLI.

Lummox

12,775 görüntüleme • 1 ay önce

Spent the day testing Claude Opus 4.7. Last month I built a design director agent for OpenClaw and now it cooks. 15 minutes in, Paper Design MCP + Claude Code had made me a rough draft. In under an hour, a Framer worthy site. My workflow: 1. Feed my agent references so it can extract design systems and lock in on my taste 2. Claude Code calls Paper Design MCP to generate the visual system (just keep the Paper app open) 3. Paper exports the assets and Claude Code then preps the build docs 4. Agent loops back, critiques, iterates Got no clue why anyone is paying $10K for a website anymore. It’s easy now.

Spent the day testing Claude Opus 4.7. Last month I built a design director agent for OpenClaw and now it cooks. 15 minutes in, Paper Design MCP + Claude Code had made me a rough draft. In under an hour, a Framer worthy site. My workflow: 1. Feed my agent references so it can extract design systems and lock in on my taste 2. Claude Code calls Paper Design MCP to generate the visual system (just keep the Paper app open) 3. Paper exports the assets and Claude Code then preps the build docs 4. Agent loops back, critiques, iterates Got no clue why anyone is paying $10K for a website anymore. It’s easy now.

klöss

14,629 görüntüleme • 5 ay önce

I switched my Hermes agent to 100% free local models with Magnitude It’s running Qwen 3.6 35B-A3B at ~60 tok/s on my DGX Spark. It’s free, private, and always on running background tasks Hermes set Magnitude up itself. With the CLI it: - Profiled my hardware and found the best models for it - Walked me through the options and let me decide - Switched itself over From there, models load just in time as the agent works and unload when idle Works with Pi, OpenCode, Hermes, OpenClaw, Codex, Claude Code, Oh My Pi, and Cline Copy this prompt and send it to your agent: “Set up local models for me with the Magnitude CLI. Install it with `npm i -g @magnitudedev/cli` (or my package manager), then run `magnitude docs onboarding` and follow the instructions” GitHub:

I switched my Hermes agent to 100% free local models with Magnitude It’s running Qwen 3.6 35B-A3B at ~60 tok/s on my DGX Spark. It’s free, private, and always on running background tasks Hermes set Magnitude up itself. With the CLI it: - Profiled my hardware and found the best models for it - Walked me through the options and let me decide - Switched itself over From there, models load just in time as the agent works and unload when idle Works with Pi, OpenCode, Hermes, OpenClaw, Codex, Claude Code, Oh My Pi, and Cline Copy this prompt and send it to your agent: “Set up local models for me with the Magnitude CLI. Install it with `npm i -g @magnitudedev/cli` (or my package manager), then run `magnitude docs onboarding` and follow the instructions” GitHub:

Tom Greenwald

22,752 görüntüleme • 1 ay önce

Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣

Opus 5.5 makes this AI stack look f…cking illegal 10 GitHub repos for building everything around the model 01 zen-mcp-server ▸ → your agent debates Gemini, GPT and local models mid-task 02 claude-context ▸ → semantic code search so the agent stops grepping blind 03 wshobson/agents ▸ → a roster of subagents, each with one narrow job 04 mcp-agent ▸ → workflow patterns built around MCP tools, not around chat 05 Backlog.md ▸ → tasks live in git, so the agent and you read the same board 06 Claude Code Development Kit ▸ → hooks, subagents and MCP wired for context at scale 07 agent-rules ▸ → shared guardrails the agent inherits in every repo 08 Agent Skills ▸ → one file that teaches the agent a job, portable across tools 09 agent-scan ▸ → scans your agents, MCP servers and skills for what leaks 10 awesome-claude-code-toolkit ▸ → the map: agents, skills, commands, hooks, MCP configs the architecture: rules → context → subagents → tools → state → review → scan I'd split the stack like this: context: claude-context → Development Kit work: wshobson/agents → mcp-agent → zen-mcp-server state: Backlog.md safety: agent-rules → Agent Skills → agent-scan everyone posts the SDK and the CLI the layer that decides whether your agent survives a week is this one the model is one folder in the stack ⭣

rody

18,089 görüntüleme • 4 gün önce

🚀 Big news: Cline just launched the MCP Marketplace -- now you can one-click install MCP servers and give Cline access to a whole new suite of tools! What's changing with the MCP Marketplace: • Browse AI capabilities like apps • One-click MCP server installation • Automatic setup and configuration • No more JSON wrestling Before: - Find GitHub repos - Read technical docs - Configure manually - Hope it works Now: - Open Cline - Browse marketplace - Click "Install" - Start using The impact: Making AI superpowers accessible to everyone, not just tech experts. Imagine giving your AI instant access to: • Web searching capabilities • Design tools integration • Code analysis powers • And much more For developers: Want to list your MCP server? Create an issue in our mcp-marketplace repo with: • GitHub repo URL • 400x400 PNG logo • Brief description The future of AI development isn't about complex integrations. It's about unlocking capabilities with a single click. Welcome to that future. 🔮

Cline

112,069 görüntüleme • 1 yıl önce

Claude Code is now scary good at full-stack! I asked it to build a real-time weather intelligence dashboard with an interactive 3D globe and a forecasting layer that predicts weather 3 days ahead. It came back with a spinning globe that has a day/night cycle using NASA satellite imagery, city lights on the dark side, weather icons that switch between sun and moon based on local time, and a time travel slider that scrubs through 10 days of data. Claude Code built the whole thing in a single session, including the backend, database, data pipeline, and frontend. For the database, I needed something fast for time-series workloads since the app ingests hourly weather readings across many cities and serves time-range queries on every slider interaction. I used Tiger Cloud by Tiger Data - Creators of TimescaleDB, which gives you managed TimescaleDB on the Postgres you already know. Claude Code connected to it through the Tiger CLI MCP server and set up the entire backend directly: - Provisioned the database service - Created hypertables for time-partitioned weather storage - Set up continuous aggregates for pre-computed rollups - Built the data ingestion pipeline and the full NextJS + ThreeJS frontend The time travel slider queries thousands of rows on every position change. On a regular Postgres table, this would require manual partitioning and index tuning to stay fast as data grows. TimescaleDB partitions the data by timestamp automatically, so each query only hits the relevant time chunk. Continuous aggregates serve the trend charts and forecast layer from pre-computed rollups instead of rescanning raw data on every request. The video below shows the final build in action, and I worked with the Tiger Data team to put this together. Tiger CLI is open-source (Apache 2.0) and works with Claude Code, Cursor, Codex, Gemini CLI, and VS Code. To try this yourself: → Sign up for Tiger Cloud (I have shared the link in the replies). It gives you $1,000 free credits (no card needed) → Install Tiger CLI: curl -fsSL https(:)//cli(.)tigerdata(.)com | sh → Run tiger mcp install claude-code → Give Claude Code a prompt and let it build Find the sign-up link in the replies.

Claude Code is now scary good at full-stack! I asked it to build a real-time weather intelligence dashboard with an interactive 3D globe and a forecasting layer that predicts weather 3 days ahead. It came back with a spinning globe that has a day/night cycle using NASA satellite imagery, city lights on the dark side, weather icons that switch between sun and moon based on local time, and a time travel slider that scrubs through 10 days of data. Claude Code built the whole thing in a single session, including the backend, database, data pipeline, and frontend. For the database, I needed something fast for time-series workloads since the app ingests hourly weather readings across many cities and serves time-range queries on every slider interaction. I used Tiger Cloud by Tiger Data - Creators of TimescaleDB, which gives you managed TimescaleDB on the Postgres you already know. Claude Code connected to it through the Tiger CLI MCP server and set up the entire backend directly: - Provisioned the database service - Created hypertables for time-partitioned weather storage - Set up continuous aggregates for pre-computed rollups - Built the data ingestion pipeline and the full NextJS + ThreeJS frontend The time travel slider queries thousands of rows on every position change. On a regular Postgres table, this would require manual partitioning and index tuning to stay fast as data grows. TimescaleDB partitions the data by timestamp automatically, so each query only hits the relevant time chunk. Continuous aggregates serve the trend charts and forecast layer from pre-computed rollups instead of rescanning raw data on every request. The video below shows the final build in action, and I worked with the Tiger Data team to put this together. Tiger CLI is open-source (Apache 2.0) and works with Claude Code, Cursor, Codex, Gemini CLI, and VS Code. To try this yourself: → Sign up for Tiger Cloud (I have shared the link in the replies). It gives you $1,000 free credits (no card needed) → Install Tiger CLI: curl -fsSL https(:)//cli(.)tigerdata(.)com | sh → Run tiger mcp install claude-code → Give Claude Code a prompt and let it build Find the sign-up link in the replies.

Avi Chawla

14,838 görüntüleme • 4 ay önce

Important new course: Agent Skills with Anthropic, built with Anthropic and taught by Elie Schoppik! Skills are constructed as folders of instructions that equip agents with on-demand knowledge and workflows. This short course teaches you how to create them following best practices. Because skills follow an open standard format, you can build them once and deploy across any skills-compatible agent, like Claude Code. What you'll learn: - Create custom skills for code generation and review, data analysis, and research - Build complex workflows using Anthropic's pre-built skills (Excel, PowerPoint, skill creation) and custom skills - Combine skills with MCP and subagents to create agentic systems with specialized knowledge - Deploy the same skills across Claude Code, the Claude API, and the Claude Agent SDK Join and learn to equip agents with the specialized knowledge they need for reliable, repeatable workflows.

Important new course: Agent Skills with Anthropic, built with Anthropic and taught by Elie Schoppik! Skills are constructed as folders of instructions that equip agents with on-demand knowledge and workflows. This short course teaches you how to create them following best practices. Because skills follow an open standard format, you can build them once and deploy across any skills-compatible agent, like Claude Code. What you'll learn: - Create custom skills for code generation and review, data analysis, and research - Build complex workflows using Anthropic's pre-built skills (Excel, PowerPoint, skill creation) and custom skills - Combine skills with MCP and subagents to create agentic systems with specialized knowledge - Deploy the same skills across Claude Code, the Claude API, and the Claude Agent SDK Join and learn to equip agents with the specialized knowledge they need for reliable, repeatable workflows.

Andrew Ng

890,490 görüntüleme • 8 ay önce

Agentic coding puts a kind of stress on GPU clusters that providers are struggling to handle. SemiAnalysis runs it on the clusters it rates anyway, with an open-source CLI in front. "A lot of our ClusterMAX testing, we lead with our CLI, cmax. It's open source. Feel free to try it out on your managed cluster." "We do use agentic coding for testing all these clusters, and the workload is very different. The workload is very stressful on these systems." "That's why we have cmax CLI as a front end, and the agent is just a wrap around it. If there are any issues cmax CLI faces, the agent debugs into it and understands what's going on."

Agentic coding puts a kind of stress on GPU clusters that providers are struggling to handle. SemiAnalysis runs it on the clusters it rates anyway, with an open-source CLI in front. "A lot of our ClusterMAX testing, we lead with our CLI, cmax. It's open source. Feel free to try it out on your managed cluster." "We do use agentic coding for testing all these clusters, and the workload is very different. The workload is very stressful on these systems." "That's why we have cmax CLI as a front end, and the agent is just a wrap around it. If there are any issues cmax CLI faces, the agent debugs into it and understands what's going on."

SemiAnalysis

22,841 görüntüleme • 9 gün önce

Why I use Cline - a free VS Code plugin - for AI engineering. Saoud Rizwan has: Flexible context management: It lets you include only what's relevant, making it ideal for large codebases. Attach files, folders, URLs and problems. Visualizes how much of the context window you've used too. Model flexibility: Cline isn't tied to one provider; it supports models from Anthropic, DeepSeek, Google Gemini, OpenAI, local models (via ollama or LM Studio) and more, allowing you to switch models for cost efficiency and capability. Plan/Act Modes: The v3.2.6 update introduces modes for designing solutions (Plan) or direct implementation (Act), providing control when you need it most. DeepSeek-R1 (Plan) + Claude 3.5 Sonnet (Act) workflow: This hybrid approach can reduce costs by up to 97% while improving output quality. DeepSeek as an architect, Sonnet for implementation. Checkpoints: Beyond git, Cline captures workspace states, offering granular rollback and comparison, especially useful for exploring solutions or debugging. Runtime awareness: Cline's integration with running systems is a game-changer, allowing real-time interaction with browsers (automatically check UI, interactions) and terminals to verify changes. Model Context Protocol (MCP): This allows for custom tool integration, making Cline extensible for specific enterprise needs without complex prompt engineering. How does it compare to alternatives? Cline shines with its system-level integration, model flexibility, and control, though it requires more attention to model selection and cost. My take: Cline aligns with professional engineering practices, offering control, visibility, and extensibility for complex system development. Totally worth considering for serious engineering teams.

Why I use Cline - a free VS Code plugin - for AI engineering. Saoud Rizwan has: Flexible context management: It lets you include only what's relevant, making it ideal for large codebases. Attach files, folders, URLs and problems. Visualizes how much of the context window you've used too. Model flexibility: Cline isn't tied to one provider; it supports models from Anthropic, DeepSeek, Google Gemini, OpenAI, local models (via ollama or LM Studio) and more, allowing you to switch models for cost efficiency and capability. Plan/Act Modes: The v3.2.6 update introduces modes for designing solutions (Plan) or direct implementation (Act), providing control when you need it most. DeepSeek-R1 (Plan) + Claude 3.5 Sonnet (Act) workflow: This hybrid approach can reduce costs by up to 97% while improving output quality. DeepSeek as an architect, Sonnet for implementation. Checkpoints: Beyond git, Cline captures workspace states, offering granular rollback and comparison, especially useful for exploring solutions or debugging. Runtime awareness: Cline's integration with running systems is a game-changer, allowing real-time interaction with browsers (automatically check UI, interactions) and terminals to verify changes. Model Context Protocol (MCP): This allows for custom tool integration, making Cline extensible for specific enterprise needs without complex prompt engineering. How does it compare to alternatives? Cline shines with its system-level integration, model flexibility, and control, though it requires more attention to model selection and cost. My take: Cline aligns with professional engineering practices, offering control, visibility, and extensibility for complex system development. Totally worth considering for serious engineering teams.

Addy Osmani

53,487 görüntüleme • 1 yıl önce

Another blow to Anthropic! They spent months building what's now fully open-source. Anthropic recently put Claude inside Slack, where you can tag it in a channel. It reads the thread, breaks the task into steps, and posts the result back. The problem is that it only runs Claude and only in the channels Anthropic supports. Running your own agent there is harder. The reasoning, tool calls, and state management are mostly handled by the framework. Connecting that agent to a messaging platform is not. Moreover, each platform has a different integration: - Slack renders messages with Block Kit - Teams uses Adaptive Cards - and each has its own SDK, auth flow, and delivery model. If an agent needs to run on three platforms, one must write three separate integrations against the same agent logic. That overhead explains why most custom agents never get deployed to Slack, and why the ones that do are usually a single vendor's hosted assistant. The alternative is to keep the agent in one place and add a per-platform adapter that translates its output into each platform's native format. The agent is written once, and each channel requires just another output target instead of a separate build. CopilotKit open-sourced this full implementation in the Channels SDK. Essentially, any agent that implements AG-UI can run in a messaging platform in a few lines of code, like Slack, Teams, Discord, WhatsApp, and many more. Because the agent runs inside the thread, it has that conversation's context, so it can summarize the discussion, open a ticket, or route to the right person. It works with any backend, so LangGraph, CrewAI, Mastra, Google ADK, or a plain HTTP agent can connect through an existing endpoint. The same message can render as a Block Kit in Slack and as Adaptive Cards in Teams. In practice, the model and orchestration stay the same; it requires no migration or rewrite. It also handles human-in-the-loop approvals, persistence, and transcripts that carry state across platforms, so a thread started in Teams can continue in Slack. CopilotKit is open-source, and AG-UI is supported across every major agent framework, including LangGraph, CrewAI, Mastra, and Google ADK. Here's the repo: (don't forget to star it ⭐) The agent running in Slack no longer has to be a vendor's. It can be the one you already built. The video below shows this in action. Thanks to CopilotKit for working with me on this launch.

Another blow to Anthropic! They spent months building what's now fully open-source. Anthropic recently put Claude inside Slack, where you can tag it in a channel. It reads the thread, breaks the task into steps, and posts the result back. The problem is that it only runs Claude and only in the channels Anthropic supports. Running your own agent there is harder. The reasoning, tool calls, and state management are mostly handled by the framework. Connecting that agent to a messaging platform is not. Moreover, each platform has a different integration: - Slack renders messages with Block Kit - Teams uses Adaptive Cards - and each has its own SDK, auth flow, and delivery model. If an agent needs to run on three platforms, one must write three separate integrations against the same agent logic. That overhead explains why most custom agents never get deployed to Slack, and why the ones that do are usually a single vendor's hosted assistant. The alternative is to keep the agent in one place and add a per-platform adapter that translates its output into each platform's native format. The agent is written once, and each channel requires just another output target instead of a separate build. CopilotKit open-sourced this full implementation in the Channels SDK. Essentially, any agent that implements AG-UI can run in a messaging platform in a few lines of code, like Slack, Teams, Discord, WhatsApp, and many more. Because the agent runs inside the thread, it has that conversation's context, so it can summarize the discussion, open a ticket, or route to the right person. It works with any backend, so LangGraph, CrewAI, Mastra, Google ADK, or a plain HTTP agent can connect through an existing endpoint. The same message can render as a Block Kit in Slack and as Adaptive Cards in Teams. In practice, the model and orchestration stay the same; it requires no migration or rewrite. It also handles human-in-the-loop approvals, persistence, and transcripts that carry state across platforms, so a thread started in Teams can continue in Slack. CopilotKit is open-source, and AG-UI is supported across every major agent framework, including LangGraph, CrewAI, Mastra, and Google ADK. Here's the repo: (don't forget to star it ⭐) The agent running in Slack no longer has to be a vendor's. It can be the one you already built. The video below shows this in action. Thanks to CopilotKit for working with me on this launch.

Akshay 🚀

244,387 görüntüleme • 2 ay önce

This GitHub repo is gold for anyone running Claude Code/ Codex / Any coding agent at all. My usage limits almost last double since I started using this. An open source context layer that stops your agent from reading 40 files to answer one question. No API key, no billing, no rate limit tiers. Benchmarked against Claude Code baseline: 27x token efficiency, 36% lower cost, 89% fewer file reads, 49% fewer tool calls. Every number is reproducible, the harness is in the repo. 3.5k+ stars. 50k+ pip installs, 30+ contributors, works with Claude Code, Cursor and VS Code out of the box. pip install repowise and point it at your codebase.

This GitHub repo is gold for anyone running Claude Code/ Codex / Any coding agent at all. My usage limits almost last double since I started using this. An open source context layer that stops your agent from reading 40 files to answer one question. No API key, no billing, no rate limit tiers. Benchmarked against Claude Code baseline: 27x token efficiency, 36% lower cost, 89% fewer file reads, 49% fewer tool calls. Every number is reproducible, the harness is in the repo. 3.5k+ stars. 50k+ pip installs, 30+ contributors, works with Claude Code, Cursor and VS Code out of the box. pip install repowise and point it at your codebase.

Srishti

12,998 görüntüleme • 2 ay önce

CLAUDE CODE IS NOW FREE AND YOU CAN BUILD AN ENTIRE AI CODING SYSTEM WITH 1M CONTEXT, AGENT OS AND OBSIDIAN MEMORY WITHOUT PAYING FOR ANY OF IT. The stack gets smarter over time and costs you nothing to run.

CLAUDE CODE IS NOW FREE AND YOU CAN BUILD AN ENTIRE AI CODING SYSTEM WITH 1M CONTEXT, AGENT OS AND OBSIDIAN MEMORY WITHOUT PAYING FOR ANY OF IT. The stack gets smarter over time and costs you nothing to run.

0xMarioNawfal

51,265 görüntüleme • 4 ay önce

$Data encryption is now live on Veilnet. Available in @veilnet/mcp-server@0.3.0. Any blob — file, dataset, config, recovery codes, contract draft, research note, agent memory — can now be encrypted on your device, shipped to Veilnet as ciphertext, and fetched back later without the decryption key ever leaving your machine. Three new MCP tools are live: data_store({ label, data }) encrypt + store data on Veilnetdata_fetch({ id }) fetch + decrypt locallydata_list() list stored ids With labels kept encrypted, the flow is simple: user data → encrypted locally → ciphertext stored on Veilnet → key remains on user device → agent fetches when needed → local decryption onlyVeilnet sees encrypted blobs. Your AI agent gets persistent private memory and secure storage.The provider does not need the raw data. This works in Claude Code, Claude Desktop, Cursor, Continue, and Cline. Install: npm i -g @veilnet/mcp-server Bootstrap your key at: → Agent tab Then ask any MCP-aware agent:“store this encrypted on Veilnet.”Docs:docs.veilnet.toPrivate prompts protected what users ask. Private MCP protected what agents run. Wallet Context protected what agents read. Encrypted data storage now protects what agents remember and reuse. All powered by $VEILNET$

Data encryption is now live on Veilnet. Available in @veilnet/[email protected]. Any blob — file, dataset, config, recovery codes, contract draft, research note, agent memory — can now be encrypted on your device, shipped to Veilnet as ciphertext, and fetched back later without the decryption key ever leaving your machine. Three new MCP tools are live: data_store({ label, data }) encrypt + store data on Veilnetdata_fetch({ id }) fetch + decrypt locallydata_list() list stored ids With labels kept encrypted, the flow is simple: user data → encrypted locally → ciphertext stored on Veilnet → key remains on user device → agent fetches when needed → local decryption onlyVeilnet sees encrypted blobs. Your AI agent gets persistent private memory and secure storage.The provider does not need the raw data. This works in Claude Code, Claude Desktop, Cursor, Continue, and Cline. Install: npm i -g @veilnet/mcp-server Bootstrap your key at: → Agent tab Then ask any MCP-aware agent:“store this encrypted on Veilnet.”Docs:docs.veilnet.toPrivate prompts protected what users ask. Private MCP protected what agents run. Wallet Context protected what agents read. Encrypted data storage now protects what agents remember and reuse. All powered by $VEILNET

Veilnet

11,761 görüntüleme • 4 ay önce

Claude Code is now scary good at full-stack! I asked it to build a real-time weather intelligence dashboard with an interactive 3D globe, a forecasting layer that predicts weather 3 days ahead, and an anomaly detector that flags cities whose weather is behaving abnormally. It came back with a spinning globe that has a day/night cycle using NASA satellite imagery, city lights on the dark side, weather icons that switch between sun and moon based on local time, and a time travel slider that scrubs through 10 days of data. And when a city's weather breaks from its own normal, it pulses red (abnormally hot) or blue (abnormally cold) right on the globe, updating live and reflecting the anomaly state at any point you drag the slider to. Claude Code built the whole thing in a single session, including the backend, database, data pipeline, and frontend. For the database, I needed something fast for time-series workloads since the app ingests hourly weather readings across many cities and serves time-range queries on every slider interaction. I used Tiger Cloud by Tiger Data - Creators of TimescaleDB, which gives you managed TimescaleDB on the Postgres you already know. Claude Code connected to it through the Tiger CLI MCP server and set up the entire backend directly: - Provisioned the database service - Created hypertables for time-partitioned weather storage - Set up continuous aggregates for pre-computed rollups - Built the data ingestion pipeline and the full NextJS + ThreeJS frontend The time travel slider queries thousands of rows on every position change. On a regular Postgres table, this would require manual partitioning and index tuning to stay fast as data grows. TimescaleDB partitions the data by timestamp automatically, so each query only hits the relevant time chunk. Continuous aggregates serve the trend charts, the forecast layer, and the anomaly baselines from pre-computed rollups instead of rescanning raw data on every request. The video below shows the final build in action, and I worked with the Tiger Data team to put this together. Tiger CLI is open-source (Apache 2.0) and works with Claude Code, Cursor, Codex, Gemini CLI, and VS Code. To try this yourself: → Sign up for Tiger Cloud (I have shared the link in the replies). It gives you $1,000 free credits (no card needed) → Install Tiger CLI: curl -fsSL https(:)//cli(.)tigerdata(.)com | sh → Run tiger mcp install claude-code → Give Claude Code a prompt and let it build sign-up here: My co-founder also wrote a detailed article on this. The article is quoted below.

Claude Code is now scary good at full-stack! I asked it to build a real-time weather intelligence dashboard with an interactive 3D globe, a forecasting layer that predicts weather 3 days ahead, and an anomaly detector that flags cities whose weather is behaving abnormally. It came back with a spinning globe that has a day/night cycle using NASA satellite imagery, city lights on the dark side, weather icons that switch between sun and moon based on local time, and a time travel slider that scrubs through 10 days of data. And when a city's weather breaks from its own normal, it pulses red (abnormally hot) or blue (abnormally cold) right on the globe, updating live and reflecting the anomaly state at any point you drag the slider to. Claude Code built the whole thing in a single session, including the backend, database, data pipeline, and frontend. For the database, I needed something fast for time-series workloads since the app ingests hourly weather readings across many cities and serves time-range queries on every slider interaction. I used Tiger Cloud by Tiger Data - Creators of TimescaleDB, which gives you managed TimescaleDB on the Postgres you already know. Claude Code connected to it through the Tiger CLI MCP server and set up the entire backend directly: - Provisioned the database service - Created hypertables for time-partitioned weather storage - Set up continuous aggregates for pre-computed rollups - Built the data ingestion pipeline and the full NextJS + ThreeJS frontend The time travel slider queries thousands of rows on every position change. On a regular Postgres table, this would require manual partitioning and index tuning to stay fast as data grows. TimescaleDB partitions the data by timestamp automatically, so each query only hits the relevant time chunk. Continuous aggregates serve the trend charts, the forecast layer, and the anomaly baselines from pre-computed rollups instead of rescanning raw data on every request. The video below shows the final build in action, and I worked with the Tiger Data team to put this together. Tiger CLI is open-source (Apache 2.0) and works with Claude Code, Cursor, Codex, Gemini CLI, and VS Code. To try this yourself: → Sign up for Tiger Cloud (I have shared the link in the replies). It gives you $1,000 free credits (no card needed) → Install Tiger CLI: curl -fsSL https(:)//cli(.)tigerdata(.)com | sh → Run tiger mcp install claude-code → Give Claude Code a prompt and let it build sign-up here: My co-founder also wrote a detailed article on this. The article is quoted below.

Akshay 🚀

37,269 görüntüleme • 1 ay önce

Reviewing AI-generated code is the new bottleneck. Writing code was slow before. Now, in a few minutes, you can generate virtually unlimited lines of code using AI. But developers are now spending 70% of their time checking that code. That's the new bottleneck. I've been using Cline, and they have a feature that actually helps with this: You can click a button and have Cline generate an inline explanation for every single line of AI-generated code. Take a look at the attached video. What it does: 1. You can read the code and the explanation together 2. You don't lose context while reviewing code 3. You understand the "why" behind each change And here is the best part: It works on any git diff. You can use it to review PRs, understand commits from other people, or catch up on a codebase you haven't touched in a while.

Reviewing AI-generated code is the new bottleneck. Writing code was slow before. Now, in a few minutes, you can generate virtually unlimited lines of code using AI. But developers are now spending 70% of their time checking that code. That's the new bottleneck. I've been using Cline, and they have a feature that actually helps with this: You can click a button and have Cline generate an inline explanation for every single line of AI-generated code. Take a look at the attached video. What it does: 1. You can read the code and the explanation together 2. You don't lose context while reviewing code 3. You understand the "why" behind each change And here is the best part: It works on any git diff. You can use it to review PRs, understand commits from other people, or catch up on a codebase you haven't touched in a while.

Santiago

64,438 görüntüleme • 10 ay önce