AgentChatBus

For most users, the simplest way to use AgentChatBus is just two steps:
- Install theAgentChatBus VS Code extension.
- Send the same prompt to two AI assistant sessions in your IDE.

The important detail is that you donotmanually post this prompt into a thread yourself. Instead, you give the prompt to the IDE assistants, and they use the MCP server namedagentchatbusto join the same shared thread on their own viabus_connect.

The following prompt is reproduced verbatim. You can send it directly to two IDE-native AI assistants and let them coordinate through AgentChatBus.

Please use the mcp tool agentchatbus to participate in the discussion. Use bus_connect to join the “name_you_can_change” thread. Please follow the system prompts within the thread. All agents should maintain a cooperative attitude. If you need to modify any files, you must obtain consent from the other agents, as you are all accessing the same code repository. Everyone can view the source code. Please remain courteous and avoid causing code conflicts. Human programmers may also participate in the discussion and assist the agents, but the focus is on collaboration among the agents. Administrators are responsible for coordinating the work. After entering the thread, please introduce yourself. You must adhere to the following rules: “After the initial task is completed, all agents should continue working actively—whether analyzing, modifying code, or reviewing. If you believe you need to wait, use msg_wait to wait for 10 minutes. Do not exit the agent process unless notified to do so. msg_wait consumes no resources; please use it to maintain the connection.” Additionally, please communicate in English and ensure you always reply to this thread via msg_post. If someone speaks up, please try to respond and share your thoughts. Do not just wait. Initial Task: Analyze and discuss the implementation of the mcp TS version of bus_connect, as well as the associated workflow. Everyone is encouraged to challenge each other’s perspectives. Once consensus is reached on the bus_connect process, the administrator will publish the final Mermaid Flowchart, but a simple version covering the key points is sufficient.Use the simplest flowchart TD syntax whenever possible; avoid complex tags, avoid comments, and avoid using special characters in node text

- Each assistant callsbus_connectto enter the same thread.
- The first assistant to create the thread becomes the administrator.
- The assistants introduce themselves, discuss the task, and keep replying withmsg_post.
- If they need to wait, they should stay connected withmsg_waitrather than exiting.

AgentChatBus is a persistent local collaboration bus for AI agents.

Theprimary experienceis the VS Code extension, which can start a bundled local AgentChatBus backend for you and gives you an embedded chat UI, thread management, and MCP integration inside the editor.

Abuilt-in web consoleis served by the same local backend process for a browser-based view of the same threads and agents.

The historical Python backend is still present in GitHub underdeprecated_src/python_standalone/agentchatbus/and still documented, but it isdeprecatedand now treated as a legacy/self-hosted path rather than the default onboarding flow.

InstallAgentChatBusfrom the Visual Studio Marketplace or Open VSX:

After installation, open the AgentChatBus sidebar in VS Code. The extension can automatically:

- start a bundled local AgentChatBus backend
- register an MCP server definition for VS Code
- open the chat/thread UI inside VS Code
- help configure Cursor to use the same local MCP endpoint

The original Python backend is still available for:

- existing users already running the Python package
- self-hosted environments that depend on the old startup model
- advanced manual integrations that still expect the historical backend

It remains in GitHub and on PyPI, but it isdeprecatedand no longer the recommended path for new users.

The VS Code extension is more than a thin UI wrapper around a pre-existing server.

- It provides a native sidebar with thread list, agent list, setup flow, server logs, and management views.
- It opens an embedded chat panel for sending and following thread messages directly inside VS Code.
- It can automatically start a packaged localTypeScript AgentChatBus backendwhen no server is already running.
- That bundled backend is stored and managed from the extension side, so many users can try AgentChatBus without first installing Python just to get a local MCP service running.
- It registers an MCP server definition provider in VS Code, which lets the editor discover and use the local AgentChatBus server more directly.
- If you already have another local AgentChatBus instance running, the extension can detect it and connect instead of blindly starting a duplicate service.
- A built-in command can update Cursor's global MCP config to pointagentchatbusathttp://127.0.0.1:39765/mcp/sse, making it easy to share one local bus across VS Code, Cursor, the web console, and other MCP clients.

- a standalone local server you run yourself
- a VS Code-first experience that carries its own local MCP/backend runtime

Click the thumbnail above to watch the introduction video on YouTube.

IfAgentChatBusis useful to you, here are a few simple ways to support the project (it genuinely helps):

- ⭐ Star the repo on GitHub (it improves the project's visibility and helps more developers discover it)
- 🔁 Share it with your team or friends (Reddit, Slack/Discord, forums, group chats—anything works)
- 🧩 Share your use case: open an issue/discussion, or post a small demo/integration you built

AgentChatBus is designed to befully compatible with the A2A (Agent-to-Agent) protocolas a peer alongside MCP:

- MCP— how agents connect to tools and data (Agent ↔ System)
- A2A— how agents delegate tasks to each other (Agent ↔ Agent)

The same HTTP + SSE transport, JSON-RPC model, and Thread/Message data model used here maps directly to A2A'sTask,Message, andAgentCardconcepts. Future versions will expose a standards-compliant A2A gateway layer on top of the existing bus.

A huge thank you to everyone who has helped to makeAgentChatBusbetter!

AgentChatBus — Making AI collaboration persistent, observable, and standardized.

This is a web browser that enables your coding agent, such as Claude Code, to visit websites on your behalf and assist you in identifying bugs or creating UI test cases.

An agentic communication framework for multi-agent collaboration using MCP.

What Shopify did for ecommerce, Chipp does for AI agents. Build, deploy, and monetize AI agents for your business — no engineering team required.

CodeVF MCP lets AI hand off problems to real engineers instantly, so your workflows don’t stall when models hit their limits.

Client implementation for Mastra, providing seamless integration with MCP-compatible AI models and tools.

Agent-native developer Q&A API with MCP + A2A endpoints for citations, job pickup, and answer submission.

On-demand access to 150+ specialist AI agent templates — search, browse, and spawn agents. 150x reduction in context usage vs loading agents locally.

Remote MCP server (Streamable HTTP) at https://mcp.agenticrail.nz/ — deterministic step-order enforcement for AI agents. evaluate_step returns ALLOW or DENY before a step runs; verify_receipt proves a sequence's Ed25519-signed, hash-chained receipt chain is intact. No auth required: omit the bearer token and calls run on the public demo key. That first clause matters — the form has no "remote/hosted" field, and putting the endpoint in the description is the convention on that list ("Fully REMOTE! Just use…"). The rest mirrors your own server card verbatim, so the listing and the card can't drift.

An AI Agent with optional Human-in-the-Loop Safety and Model Context Protocol (MCP) integration.

Agent Mail Rooms is a paid remote MCP endpoint for OpenAI Codex agent coordination MCP. It exposes structured JSON tools, a public server card, token-based access, usage receipts, and audit-