AI Federation Network

@ruvnet

About AI Federation Network

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

Config

Add this server to your MCP-compatible client using the configuration below.

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

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

FAQ from AI Federation Network

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.

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.

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.

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.

What runtime environments are required?