What is Agents.md for?
It is a hierarchical context management system for AI agents working on long-term projects. It stores project-wide and task-wide context, isolates subagents to prevent overload, and persists knowledge across sessions.
A
Agents.md MCP Server
@benhaotang
基本信息
关于 Agents.md MCP Server
Minimal MCP (Model Context Protocol) HTTP server for AGENTS.md and structured tasks, with versioned history (logs/revert) and an ephemeral scratchpad, exposed over a Streamable HTTP endpoint. The scratchpad can also be used to spawn context isolated subagents (via Gemini, OpenAI,
Agents.md MCP Server 配置
Agents.md MCP Server 工具
工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is Agents.md?
Agents.md is an MCP server that provides hierarchical context management for AI agents working on long-term projects. It stores project-wide knowledge in AGENTS.md and task-wide scratchpads, enabling persistent context across sessions and subagent isolation.
How to use Agents.md?
Install via the automatic curl script or clone the repository and run with Node or Docker. Configure required and optional environment variables (e.g., HOST, PORT, external AI provider keys). Connect any MCP client to the server’s /mcp endpoint using a user API key.
Key features of Agents.md
- Hierarchical context management (project-wide, task-wide, subagent isolation)
- Persistent knowledge across multiple chat sessions
- Supports external AI providers for subagent tools
- User and API‑key authentication for MCP endpoints
- Admin API for user creation, listing, and key rotation
- Runs locally or in Docker with persistent storage
Use cases of Agents.md
- Long-term project management where an AI agent must retain knowledge
- Multi‑session research tasks requiring accumulated context
- Collaborative workflows with subagents operating on focused context
常见问题
How do I install Agents.md?
You can use the automatic install script (Unix-like) or manually clone the repository and run with Node or Docker. See the “Automatic Install” and “Manual Install” sections in the README for detailed commands.
Does Agents.md require an external AI API?
No. Using external AI (e.g., Google, OpenAI) is optional. Set `USE_EXTERNAL_AI=true` and provide API keys only if you want subagent tools to use an external model.
Where is data persisted?
For Docker deployments, data is stored in the mounted volume (default `$HOME/.config/mcp-http-agent-md/data`). For Node-based runs, the README does not specify a default location.
How does authentication work?
MCP endpoints require a user API key supplied via `?apiKey=` query parameter or `Authorization: Bearer` header. Admin endpoints use a separate `MAIN_API_KEY` in the `Authorization` header. Users are created through the admin API.
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