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MCP Agent Server

@LeadBroaf

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

LeadBroaf

关于 MCP Agent Server

Open-source, modular “brain” for AI employees. Integrates with n8n and workflow engines, features persistent agent memory, natural language interface, and feedback loops. SaaS-ready, extensible, and easy to deploy with Docker.

#mcp-agent-server#ai-employees#workflow-automation

MCP Agent Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-agent-server": {
      "type": "http",
      "url": "http://localhost:4000"
    }
  }
}

MCP Agent 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。

点击上方按钮,直接连接服务器端点实时获取工具列表。

概览

What is MCP Agent Server?

MCP Agent Server is an open‑source, modular “brain” for AI employees/agents, designed to work seamlessly with n8n and other workflow engines. It enables users to create persistent agents with memory, feedback loops, and natural language interfaces.

How to use MCP Agent Server?

Clone the repository, copy any docs and memory folders, then build and run with docker-compose up --build. The server becomes available at http://localhost:4000. You need Node.js and Docker installed. After startup, register a user via POST /users/register, obtain an API key, and use that key to manage agents and memory endpoints.

Key features of MCP Agent Server

  • Open‑source modular “brain” for AI employees
  • Persistent, agent‑centric memory and feedback loops
  • Natural language instruction parsing and task orchestration
  • Easy deployment with Docker Compose
  • Opinionated design inspired by the “AI employee” metaphor
  • API‑based user and API key management

Use cases of MCP Agent Server

  • Building AI employees that learn from feedback and improve over time
  • Creating vertical solutions like “AI Analyst” or “AI Admin” with prebuilt skills
  • Integrating persistent agents into n8n workflows for automated task execution
  • Offering simple, non‑technical AI agent experiences for SMBs and individuals

常见问题

1

How are agents authenticated?

All endpoints except `/health`, `/users/register`, and `/users/login` require an `x-api-key` header. API keys are managed per user through dedicated endpoints.

2

How do I manage users and API keys?

Use `POST /users/register` to create a user, `POST /users/login` to get an API key, and `GET /users/me/api-keys`, `POST /users/me/api-keys`, `DELETE /users/me/api-keys/:id` to list, create, or revoke keys.

3

What are the system requirements?

Node.js and Docker must be installed. The server runs via Docker Compose and listens on port 4000 by default.

4

How does agent memory work?

Memory and feedback are persistent and agent‑centric. Use `POST /agents/:id/memory` to add memory/feedback and `GET /agents/:id/memory` to retrieve it.

5

Is the MCP Agent Server open source?

Yes, the project is open source and available on GitHub.

评论

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