ContextForge

An open source registry and proxy that federates MCP, A2A, and REST/gRPC APIs with centralized governance, discovery, and observability. Optimizes Agent & Tool calling, and supports plugins.

     

     

ContextForge is an open source registry and proxy that federates tools, agents, and APIs into one clean endpoint for your AI clients. It provides centralized governance, discovery, and observability across your AI infrastructure:

• Tools Gateway — MCP, REST, gRPC-to-MCP translation, and TOON compression
• Agent Gateway — A2A protocol, OpenAI-compatible and Anthropic agent routing
• API Gateway — Rate limiting, auth, retries, and reverse proxy for REST services
• Plugin Extensibility — 40+ plugins for additional transports, protocols, and integrations
• Observability — OpenTelemetry tracing with Phoenix, Jaeger, Zipkin, and other OTLP backends

It runs as a fully compliant MCP server, deployable via PyPI or Docker, and scales to multi-cluster environments on Kubernetes with Redis-backed federation and caching.

Table of Contents

• Overview & Goals
• Quick Start - PyPI
• Quick Start - Containers
  • Optional Web UI
• VS Code Dev Container
• Installation
• Upgrading
• Configuration
• Running
• Cloud Deployment
• API Reference
• Testing
• Project Structure
• Development
• Troubleshooting
• Contributing

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📌 Quick Links

Resource	Description
5-Minute Setup	Get started fast — uvx, Docker, Compose, or local dev
Getting Help	Support options, FAQ, community channels
Issue Guide	How to file bugs, request features, contribute
Full Documentation	Complete guides, tutorials, API reference
Deprecations	Deprecated runtime paths and migration guidance

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Overview & Goals

ContextForge is an open source registry and proxy that federates any Model Context Protocol (MCP) server, A2A server, or REST/gRPC API, providing centralized governance, discovery, and observability. It optimizes agent and tool calling, and supports plugins. See the project roadmap for more details.

It currently supports:

• Federation across multiple MCP and REST services
• A2A (Agent-to-Agent) integration for external AI agents (OpenAI, Anthropic, custom)
• gRPC-to-MCP translation via automatic reflection-based service discovery
• Virtualization of legacy APIs as MCP-compliant tools and servers
• Transport over HTTP, JSON-RPC, WebSocket, SSE (with configurable keepalive), and Streamable HTTP; stdio transport available for server-side use
• An Admin UI for real-time management, configuration, and log monitoring (with airgapped deployment support)
• A redesigned, more user-friendly Web UI that runs in a separate container
• Built-in auth, retries, and rate-limiting with user-scoped OAuth tokens and unconditional X-Upstream-Authorization header support
• OpenTelemetry observability with Phoenix, Jaeger, Zipkin, and other OTLP backends
• Scalable deployments via Docker or PyPI, Redis-backed caching, and multi-cluster federation

For a list of upcoming features, check out the ContextForge Roadmap

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• Federates any MCP server or REST API
• Lets you choose your MCP protocol version (e.g., 2025-11-25)
• Exposes a single, unified interface for diverse backends

• Wraps non-MCP services as virtual MCP servers
• Registers tools, prompts, and resources with minimal configuration
• gRPC-to-MCP translation via server reflection protocol
• Automatic service discovery and method introspection

• Adapts REST APIs into tools with:

  • Automatic JSON Schema extraction
  • Support for headers, tokens, and custom auth
  • Retry, timeout, and rate-limit policies

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