GPT MCP Proxy

GPT MCP Proxy

The GPT MCP Proxy is a lightweight REST API server that translates the Model Context Protocol (MCP) into standard HTTP endpoints. It acts as a bridge between MCP‑compliant tool servers and web clients, enabling developers to expose AI‑powered tools through familiar REST APIs. By doing so, it eliminates the need for custom adapters or deep integration work when incorporating MCP tools into GPT‑based applications that rely on webhooks, middleware, or serverless functions.

Why It Matters

Developers building AI assistants often need to call external tools—file manipulation, data retrieval, or domain‑specific APIs—without re‑implementing the tool logic in each client. MCP provides a uniform, language‑agnostic interface for such tools, but many existing AI platforms and orchestration frameworks only understand HTTP. The GPT MCP Proxy solves this mismatch: it automatically discovers available MCP servers, lists their tools, and exposes each tool as a REST endpoint that can be invoked with JSON payloads. This allows GPT assistants to perform complex actions through simple HTTP calls, preserving the modularity and extensibility of MCP while leveraging the ubiquity of REST.

Core Features

• Tool Discovery: and return comprehensive listings of MCP servers and their exposed tools, making it easy to audit available capabilities.
• Tool Introspection: Detailed metadata for each tool is accessible via , including parameter schemas and documentation.
• Execution Gateway: forwards user parameters to the underlying MCP tool and streams back results, enabling synchronous or asynchronous workflows.
• OpenAPI Support: The server automatically generates an OpenAPI 3.1.0 specification (), allowing developers to integrate the proxy into API documentation, client SDKs, or automated testing pipelines.
• Secure Exposure: An optional automatic ngrok tunnel ( and ) lets the proxy be publicly reachable over HTTPS without manual networking configuration, ideal for rapid prototyping or remote deployment.

Use Cases & Scenarios

• Custom GPT Actions: When building a GPT assistant that needs to execute file system operations, database queries, or third‑party services, the proxy turns those MCP tools into HTTP actions that GPT can invoke via its action framework.
• Microservice Orchestration: In a microservices architecture, each service can expose an MCP server; the proxy aggregates them into a single REST gateway, simplifying client code and centralizing authentication.
• Serverless Deployments: Cloud functions or containers that support HTTP can host the proxy, turning otherwise stateful MCP tools into stateless endpoints suitable for autoscaling.
• Testing & Validation: The OpenAPI spec allows automated tools to generate test suites that validate tool behavior, ensuring reliability before integration into production assistants.

Unique Advantages

• Zero‑Code Integration: Because the proxy translates MCP calls to HTTP automatically, developers can add new tools by merely updating a JSON configuration file—no code changes or redeployments are required.
• Language Agnostic: The proxy works with any MCP‑compliant tool, regardless of the underlying language or runtime, making it a universal gateway for diverse AI ecosystems.
• Rapid Prototyping: With built‑in ngrok support, the proxy can be exposed over HTTPS in minutes, enabling instant demos or stakeholder reviews without complex networking setups.

In summary, the GPT MCP Proxy turns MCP’s powerful, modular tool ecosystem into a ready‑to‑use HTTP API, bridging the gap between advanced AI assistants and conventional web architectures while preserving flexibility, security, and ease of deployment.