The Model Context Protocol (MCP) enables federated connections between AI systems and various data sources through a standardized architecture. Here’s a complete implementation following the official specification:
This implementation provides a foundation for building federated MCP systems that can scale across multiple servers while maintaining the protocol’s security and standardization requirements. The federation layer enables seamless communication between different MCP servers, allowing AI systems to maintain context while moving between different tools and datasets.
The implementation supports both local and remote connections through multiple transport mechanisms, including stdio for local process communication and HTTP with Server-Sent Events for remote connections.
Security is maintained through strict capability negotiation and user consent requirement
Model Context Protocol (MCP) with Federation Support
Simplified Integration:
- Eliminates custom connections for each data source
- Standardizes AI connections with enterprise tools
- Maintains context across federated tools and datasets
Core Components:
- Federation Controller: Manages cross-server communication
- Proxy Layer: Handles authentication between federated servers
- Identity Management: Controls access across federated instances
System Components:
- MCP Hosts: AI applications needing federated data access
- MCP Servers: Programs providing federated resource access
- MCP Clients: Components maintaining federated connections
- Federation Proxy: Manages cross-server authentication
graph TD %% Client Nodes A[MCP Client] -->|JSON-RPC| C[Federation Proxy] %% Federation Proxy C -->|Route & Auth| F[Federation Manager] %% Federation Manager F -->|Manage Connections| G[MCP Server] F -->|Manage Connections| H[Resource Server] F -->|External Federation| I[Cloud Service] %% Servers G --> J[Data Source 1] H --> K[Data Source 2] I --> L[Shared Tool Integration] %% External Communications L -->|Integration APIs| M[[External APIs]]
%% Styles
classDef client fill:#f9f,stroke:#333,stroke-width:2px;
classDef server fill:#bbf,stroke:#333,stroke-width:2px;
classDef proxy fill:#ff9,stroke:#333,stroke-width:2px;
class A,G,H client;
class C,F proxy;
class I,J,K,L server;
Implementation Areas:
- Development tools with federated code repositories
- Enterprise systems with distributed databases
- Cross-organizational content repositories
- Multi-region business tool integration
Protection Mechanisms:
- Federated authentication and authorization
- Cross-server resource isolation
- Distributed consent management
- Encrypted cross-server communication
- Granular capability control
MCP with federation support enables secure, standardized AI system integration across organizational boundaries while maintaining strict security controls and seamless data access.
federated-mcp/
├── requirements.txt
├── config/
│ ├── server_config.json
│ └── auth_config.json
├── src/
│ ├── server/
│ │ ├── __init__.py
│ │ ├── mcp_server.py
│ │ ├── federation.py
│ │ ├── transport.py
│ │ └── handlers/
│ │ ├── __init__.py
│ │ ├── resources.py
│ │ ├── prompts.py
│ │ └── tools.py
│ ├── client/
│ │ ├── __init__.py
│ │ ├── mcp_client.py
│ │ └── session.py
│ └── proxy/
│ ├── __init__.py
│ ├── proxy_server.py
│ └── router.py
└── README.md
src/server/mcp_server.py:
from mcp.server import Server
import mcp.types as types
from .handlers import ResourceHandler, PromptHandler, ToolHandler
class MCPServer:
def __init__(self, name: str):
self.server = Server(name)
self.setup_handlers()
def setup_handlers(self):
@self.server.initialize()
async def handle_initialize(options):
return {
"capabilities": {
"resources": True,
"prompts": True,
"tools": True,
"sampling": True
},
"serverInfo": {
"name": self.server.name,
"version": "1.0.0"
}
}
@self.server.initialized()
async def handle_initialized():
# Handle post-initialization tasks
pass
async def run(self, read_stream, write_stream, options):
await self.server.run(read_stream, write_stream, options)
src/server/transport.py:
import asyncio
from mcp.server import stdio
class TransportManager:
@staticmethod
async def create_stdio_transport():
return await stdio.stdio_server()
@staticmethod
async def create_sse_transport(app):
from fastapi import FastAPI
from sse_starlette.sse import EventSourceResponse
@app.get("/events")
async def events():
async def event_generator():
while True:
yield {"data": "message"}
await asyncio.sleep(1)
return EventSourceResponse(event_generator())
src/server/handlers/resources.py:
from mcp.types import Resource, TextContent
class ResourceHandler:
@staticmethod
async def list_resources():
return [
Resource(
uri="example://resource",
title="Example Resource",
description="An example resource"
)
]
@staticmethod
async def read_resource(uri: str):
return [
TextContent(
type="text",
text="Resource content"
)
]
src/client/session.py:
from mcp import ClientSession
from mcp.client.models import InitializeParams
class MCPClientSession:
def __init__(self):
self.session = None
async def initialize(self, transport):
self.session = ClientSession(transport)
await self.session.initialize(InitializeParams(
protocolVersion="2024-11-05",
capabilities={
"sampling": True
}
))
async def request(self, method: str, params: dict = None):
if not self.session:
raise RuntimeError("Session not initialized")
return await self.session.request(method, params)
src/proxy/router.py:
from typing import Dict
from mcp.server import Server
class ProxyRouter:
def __init__(self):
self.routes: Dict[str, Server] = {}
async def register_server(self, server_id: str, server: Server):
self.routes[server_id] = server
async def route_request(self, server_id: str, request: dict):
if server_id not in self.routes:
raise KeyError(f"Unknown server: {server_id}")
return await self.routes[server_id].handle_message(request)
config/server_config.json:
{
"server": {
"name": "federated-mcp",
"version": "1.0.0"
},
"transport": {
"type": "stdio",
"options": {}
},
"capabilities": {
"resources": true,
"prompts": true,
"tools": true,
"sampling": true
}
}
- Create virtual environment and install dependencies:
python -m venv venv
source venv/bin/activate
pip install -r requirements.txt
- Install the MCP SDK:
pip install mcp
- Run the server:
python -m src.server.mcp_server