AI Federation Network
About
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
Details
- Author
- ruvnet
- GitHub stars
- 65
- Downloads
- 274
- Categories
- Other
Jump to
- 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
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
AI Federation NetworkCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
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.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"ai federation network": {
"federated-mcp": {
"command": "deno",
"args": [
"run",
"--allow-net",
"--allow-env",
"--allow-read",
"--allow-write",
"--allow-run",
"src/apps/deno/server.ts"
]
}
}
}
}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
A distributed runtime system for federated AI services with edge computing capabilities.
Complete implementation following the official MCP specification:
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
Key Benefits
Simplified Integration:
- Eliminates custom connections for each data source
- Standardizes AI connections with enterprise tools
- Maintains context across federated tools and datasets
Federation Architecture
Core Components:
- Federation Controller: Manages cross-server communication
- Proxy Layer: Handles authentication between federated servers
- Identity Management: Controls access across federated instances
Basic Structure
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
Real-World Applications
Implementation Areas:
- Development tools with federated code repositories
- Enterprise systems with distributed databases
- Cross-organizational content repositories
- Multi-region business tool integration
Security Features
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.
Deno Nodejs version
complete implementation using both Deno and Node.js. Let's start with the project structure:🌐 Network Protocols
- JSON-RPC 2.0 - HTTP/REST - WebSocket⚡ Edge Computing
- Multi-provider support (Supabase, Cloudflare Workers, Fly.io) - Serverless function deployment - Real-time logs and monitoring - Auto-scaling capabilities🔐 Security
- Provider-specific authentication - Secure credential storage - Environment isolation - Access control📡 Runtime Features
- Task execution - Federation support - Intent detection - Meeting information processing - Webhook handling - Real-time status monitoring - System health checksSystem Architecture
graph TD
A[AI Federation Network] --> B[Core Runtime]
B --> C[Edge Computing]
B --> D[Network Layer]
B --> E[Security]
C --> F[Supabase]
C --> G[Cloudflare]
C --> H[Fly.io]
D --> I[JSON-RPC]
D --> J[HTTP/REST]
D --> K[WebSocket]
E --> L[Auth]
E --> M[Credentials]
E --> N[Access Control]
Getting Started
# Run the server
deno run --allow-net --allow-env --allow-read --allow-write --allow-run src/apps/deno/server.ts
License
MIT License - See LICENSE file for details.
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