MCP.so
登录
A

Agents.md

@benhaotang

关于 Agents.md

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,

基本信息

分类

AI 与智能体

传输方式

stdio

发布者

benhaotang

提交者

Jourin Town

配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块,请前往代码仓库查看安装说明。

代码仓库

工具

未检测到工具

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

FAQ from Agents.md

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.

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.

评论

AI 与智能体 分类下的更多 MCP 服务器