ContextForge MCP Server

1

Add it to Claude Code

Run this in a terminal.

Run in terminal
claude mcp add mcp-context-forge -- uvx mcp-context-forge
README.md

Model Context Protocol gateway & proxy for REST, MCP, and gRPC services

Apollos AI Gateway

Model Context Protocol gateway & proxy - unify REST, MCP, and A2A with federation, virtual servers, retries, security, and an optional admin UI.

Apollos AI Gateway is a feature-rich gateway, proxy and MCP Registry that federates MCP and REST services - unifying discovery, auth, rate-limiting, observability, virtual servers, multi-transport protocols, and an optional Admin UI into one clean endpoint for your AI clients. 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.

📌 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

Overview & Goals

ContextForge is a gateway, registry, and proxy that sits in front of any Model Context Protocol (MCP) server, A2A server or REST API-exposing a unified endpoint for all your AI clients. 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), stdio and streamable-HTTP
  • An Admin UI for real-time management, configuration, and log monitoring (with airgapped deployment support)
  • 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

MCP Gateway Architecture

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


🔌 Gateway Layer with Protocol Flexibility
  • Sits in front of any MCP server or REST API
  • Lets you choose your MCP protocol version (e.g., 2025-06-18)
  • Exposes a single, unified interface for diverse backends
🧩 Virtualization of REST/gRPC Services
  • 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
🔁 REST-to-MCP Tool Adapter
  • Adapts REST APIs into tools with:

    • Automatic JSON Schema extraction
    • Support for headers, tokens, and custom auth
    • Retry, timeout, and rate-limit policies
🧠 Unified Registries
  • Prompts: Jinja2 templates, multimodal support, rollback/versioning
  • Resources: URI-based access, MIME detection, caching, SSE updates
  • Tools: Native or adapted, with input validation and concurrency controls
📈 Admin UI, Observability & Dev Experience
  • Admin UI built with HTMX + Alpine.js
  • Real-time log viewer with filtering, search, and export capabilities
  • Auth: Basic, JWT, or custom schemes
  • Structured logs, health endpoints, metrics
  • 800+ tests, Makefile targets, live reload, pre-commit hooks
🔍 OpenTelemetry Observability
  • Vendor-agnostic tracing with OpenTelemetry (OTLP) protocol sup

Environment Variables

OTEL_EXPORTER_OTLP_ENDPOINTEndpoint for OpenTelemetry observability data

Configuration

claude_desktop_config.json
{"mcpServers": {"context-forge": {"command": "uvx", "args": ["mcp-context-forge"]}}}

Try it

Federate my existing REST API and local MCP server into a single endpoint using ContextForge.
Configure a virtual MCP server to wrap my legacy gRPC service for use in Claude.
Set up rate-limiting and authentication for my federated MCP services.
Monitor the traffic and logs of my connected MCP tools using the Admin UI.

Frequently Asked Questions

What are the key features of ContextForge?

Federation across multiple MCP and REST services. gRPC-to-MCP translation via automatic reflection. Virtualization of legacy APIs as MCP-compliant tools. Built-in auth, retries, and rate-limiting. OpenTelemetry observability for all proxied traffic.

What can I use ContextForge for?

Unifying multiple disparate MCP servers into one endpoint for AI agents. Exposing legacy REST or gRPC APIs as tools within the Model Context Protocol. Adding centralized security and rate-limiting to internal AI tool infrastructure. Observing and debugging AI agent tool calls using OpenTelemetry backends.

How do I install ContextForge?

Install ContextForge by running: uvx mcp-context-forge

What MCP clients work with ContextForge?

ContextForge works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Turn this server into reusable context

Keep ContextForge docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Need the old visual installer? Open Conare IDE.
Open Conare