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AI Frameworks · IBM

mcp-context-forge

ContextForge is an open-source AI gateway and registry (Apache 2.0) that unifies MCP, REST, and gRPC APIs behind a single endpoint with centralized governance, discovery, and observability. Built by IBM in Python with FastAPI, it handles tool federation, agent routing, and plugin extensibility for complex AI infrastructure.

Source: GitHub — github.com/IBM/mcp-context-forge
4k
GitHub stars
740
Forks
Python
Primary language
Apache-2.0
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
RepositoryIBM/mcp-context-forge
OwnerIBM
Primary languagePython
LicenseApache-2.0 — OSI-approved
Stars4k
Forks740
Open issues1.1k
Latest releasev1.0.5 (2026-07-07)
Last updated2026-07-07
Sourcehttps://github.com/IBM/mcp-context-forge

What mcp-context-forge is

Python-based async gateway (FastAPI, asyncio) that proxies Model Context Protocol servers, A2A agents, and REST/gRPC services. Features OpenTelemetry tracing, Redis-backed caching, JWT/OAuth auth, rate-limiting, and Kubernetes-ready deployment. Includes 40+ plugins, automatic gRPC-to-MCP translation via reflection, and TOON compression.

Quickstart

Get the mcp-context-forge source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/IBM/mcp-context-forge.gitcd mcp-context-forge# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Multi-Agent AI Infrastructure

Consolidate multiple MCP servers, OpenAI/Anthropic agents, and REST APIs into one managed endpoint with unified discovery and observability across your AI agent ecosystem.

Enterprise API Governance

Centralize auth, rate-limiting, retries, and audit trails for legacy REST/gRPC services exposed as MCP-compliant tools, enabling guardrails without rewriting backends.

Scalable LLM Tool Orchestration

Federate tools across Kubernetes clusters with Redis caching and OTLP tracing (Phoenix, Jaeger, Zipkin), supporting high-concurrency agent workloads with distributed governance.

Implementation considerations

  • Plan auth strategy (Basic, JWT, OAuth scopes) and rate-limit policies before federation; misconfig can expose or throttle critical agents.
  • Establish naming and discovery conventions for tools, prompts, and resources to avoid collisions in large multi-team deployments.
  • Configure Redis backing for multi-cluster deployments; single-node gateway caching may not survive restarts or scale horizontally.
  • Test gRPC-to-MCP translation with target services early; automatic reflection relies on server compliance; fallback to REST adapter if issues arise.
  • Budget for OpenTelemetry backend (Phoenix, Jaeger) if observability is critical; traces are disabled by default and require explicit configuration.

When to avoid it — and what to weigh

  • Simple Single-Agent Setup — If you have one or two tools and no federation needs, ContextForge's overhead and complexity outweigh the benefit; consider direct MCP integration instead.
  • Stateless Request-Response Only — The gateway introduces statefulness (registries, caching, federation). Use a simpler reverse proxy if you only need HTTP routing without tool governance.
  • Highly Proprietary Compliance or Airgapped Isolation — Admin UI and observability features assume internet connectivity by default; airgapped deployment requires custom build and config, not straightforward out-of-box.
  • Non-Python Infrastructure — Pure Go/Rust infrastructure teams may struggle to operate, debug, and extend a Python-heavy gateway; Docker mitigates but doesn't eliminate operational friction.

License & commercial use

Apache License 2.0 (Apache-2.0). Permissive OSI-approved license allowing commercial use, modification, and distribution under same license terms. No copyleft restrictions on linked code or proprietary extensions.

Apache 2.0 permits unrestricted commercial use, including proprietary forks, provided the license notice is retained and modifications are disclosed. No vendor lock-in; you own the deployment. IBM provides the source but does not guarantee SLA or commercial support through this repository; check IBM's commercial offerings separately.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationStrong
License clarityClear
Deployment complexityModerate
DEV.co fitStrong
Assessment confidenceHigh
Security considerations

Authentication (Basic, JWT, OAuth) and rate-limiting built-in; auth headers configurable. No public audit or pen-test results mentioned in data. Review: credential rotation policy, upstream API secret storage (env vars, vaults), X-Upstream-Authorization usage, TLS config for multi-cluster federation, and plugin code provenance. Dependency review CI present but supply-chain security posture not detailed.

Alternatives to consider

LangChain / LangSmith

Agent framework + observability; simpler if you control agent code, but less federation-focused and vendor-specific (LangChain ecosystem).

Kong or Envoy (API Gateway)

Mature, language-agnostic reverse proxies with rate-limiting and auth; lack MCP-native support and tool governance but proven at scale.

Custom FastAPI Proxy

If you have in-house Python expertise, building a lightweight proxy avoids operational complexity; trades off discovery, observability, and plugin ecosystem.

Software development agency

Build on mcp-context-forge with DEV.co software developers

Deploy ContextForge today to federate agents, tools, and APIs behind one governed endpoint. Get started in 5 minutes with PyPI or Docker.

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mcp-context-forge FAQ

Do I need Kubernetes?
No. Single-node PyPI or Docker deployment works for dev/test. Kubernetes is optional for multi-cluster federation and scale; Redis-backed caching is recommended for HA.
Can I use this with Claude/GPT without OpenAI SDK?
Yes. ContextForge handles A2A protocol routing (OpenAI-compatible, Anthropic) and exposes a unified endpoint; your agent client hits the gateway instead of the vendor API directly.
What's the learning curve?
Moderate. If you know MCP, REST APIs, and basic auth (JWT/OAuth), setup is ~1 hour. gRPC-to-MCP translation and multi-cluster federation require deeper domain knowledge.
Is this production-ready?
Likely yes for single-team deployments. Active development, comprehensive tests (7,000+), and IBM backing provide confidence. Enterprise SLA or support requires separate agreement outside this repository.

Work with a software development agency

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Unify Your AI Infrastructure

Deploy ContextForge today to federate agents, tools, and APIs behind one governed endpoint. Get started in 5 minutes with PyPI or Docker.