ContextForge MCP Gateway

MCP Context Forge Gateway is a versatile, fully‑compliant MCP server that acts as a unified entry point for AI assistants to access both native MCP resources and external REST services. It solves the common problem of fragmented tool discovery, inconsistent authentication, and uneven rate‑limiting across heterogeneous backends. By federating services behind a single endpoint, developers can expose a coherent API surface to their AI clients without having to rewrite or duplicate logic for each underlying service.

At its core, the gateway performs three key functions: discovery, proxying, and registry management. Discovery aggregates MCP resources from multiple origins—local servers, remote clusters, or even REST endpoints that expose an MCP‑compatible interface—into a single catalog. Proxying forwards client requests to the appropriate target while handling authentication tokens, retry logic, and per‑service rate limits. The registry keeps track of all federated services, enabling dynamic updates without redeploying the gateway itself. This architecture eliminates the need for bespoke adapters and allows developers to add or remove services on the fly.

The gateway offers a rich set of capabilities that make it especially valuable in production AI workflows. It supports virtual servers, letting teams create isolated namespaces for different projects or environments. A Redis‑backed cache speeds up repeated lookups and reduces load on downstream services, while the optional Admin UI provides real‑time observability of request metrics, error rates, and health checks. Security is baked in with support for OAuth2, JWT validation, and fine‑grained access control lists. Additionally, the gateway is transport agnostic—it can serve MCP over HTTP, WebSocket, or any custom protocol that implements the MCP spec.

Real‑world use cases include building a chatbot that can query multiple internal databases, invoke external data‑science APIs, and call proprietary ML models—all through a single MCP endpoint. In a multi‑cluster Kubernetes deployment, the gateway can federate services across namespaces and regions, automatically routing traffic to the nearest healthy instance. For enterprises that need strict compliance, the gateway’s audit‑ready logging and rate‑limiting policies help meet regulatory requirements while still delivering low‑latency responses to AI assistants.

In summary, MCP Context Forge Gateway streamlines the integration of diverse data sources and tools into AI assistants. Its federation, security, observability, and extensibility features provide a robust foundation for building scalable, maintainable AI‑powered applications.