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AI Federation Network MCP Server

@ruvnet

基本信息

分类

其他

许可证

MIT

传输方式

stdio

作者

ruvnet

关于 AI Federation Network MCP Server

This implementation follows the official MCP specification, including proper message framing, transport layer implementation, and complete protocol lifecycle management. It provides a foundation for building federated MCP systems that can scale across multiple servers while maint

AI Federation Network MCP 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": {
    "federated-mcp": {
      "command": "deno",
      "args": [
        "run",
        "--allow-net",
        "--allow-env",
        "--allow-read",
        "--allow-write",
        "--allow-run",
        "src/apps/deno/server.ts"
      ]
    }
  }
}

AI Federation Network 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 AI Federation Network?

AI Federation Network is a distributed runtime system for federated AI services with edge computing capabilities. It implements the Model Context Protocol (MCP) to enable standardized, secure connections between AI systems and diverse data sources across organizational boundaries.

How to use AI Federation Network?

Run the server using deno run --allow-net --allow-env --allow-read --allow-write --allow-run src/apps/deno/server.ts. The system supports both local connections via stdio and remote connections via HTTP with Server-Sent Events, and includes a Federation Proxy layer for cross-server authentication.

Key features of AI Federation Network

  • Federated architecture with Controller, Proxy, and Identity Management
  • Multiple transport mechanisms: JSON‑RPC 2.0, HTTP/REST, WebSocket
  • Edge computing support for Supabase, Cloudflare Workers, and Fly.io
  • Provider‑specific authentication and secure credential storage
  • Real‑time monitoring, system health checks, and auto‑scaling
  • Capability negotiation and user consent for security

Use cases of AI Federation Network

  • Development tools accessing federated code repositories across teams
  • Enterprise systems integrating distributed databases through a unified interface
  • Cross‑organizational content repositories shared securely between partners
  • Multi‑region business tool integration with consistent access controls

常见问题

1

What is the Model Context Protocol (MCP)?

MCP is a standardized protocol enabling federated connections between AI systems and various data sources. The federation layer allows AI systems to maintain context while moving between different tools and datasets across multiple servers.

2

How does federation work in this system?

A Federation Controller manages cross‑server communication, a Proxy Layer handles authentication between federated servers, and Identity Management controls access across federated instances. The system supports strict capability negotiation and user consent for security.

3

What transport mechanisms are supported?

The implementation supports stdio for local process communication and HTTP with Server‑Sent Events (SSE) for remote connections. Additionally, the network layer includes JSON‑RPC 2.0, HTTP/REST, and WebSocket protocols.

4

What security features are included?

Security includes federated authentication and authorization, cross‑server resource isolation, distributed consent management, encrypted cross‑server communication, and granular capability control. Provider‑specific authentication and secure credential storage are also supported.

5

What runtime environments are required?

The system includes complete implementations for both Deno and Node.js. The Deno server is started with the provided command; Node.js specifics are detailed in the project structure.

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