Gin‑MCP: Zero‑Config Bridge Between Gin and the Model Context Protocol

Gin‑MCP solves a common pain point for Go developers who expose REST APIs with the popular Gin framework but also want to make those endpoints immediately consumable by MCP‑compatible AI assistants such as Claude Desktop, Cursor, or Zed. Traditionally, exposing an API to an MCP client requires writing a separate server that translates HTTP routes into the JSON schema expected by the protocol, adding authentication layers, and maintaining two codebases. Gin‑MCP eliminates this duplication by acting as a thin adapter that mounts directly onto an existing . With a single line of code, your API becomes discoverable by any MCP client without changing handler logic or adding boilerplate.

The server automatically discovers all registered routes, infers parameter and response schemas from Go types where possible, and generates a fully‑qualified MCP tool definition for each endpoint. This means that developers can start integrating AI assistants into their workflows immediately, while still benefiting from Gin’s performance and middleware ecosystem. When inference is insufficient—such as complex nested structures or custom request bodies—Gin‑MCP allows developers to register schemas manually, giving fine‑grained control over the exposed tools.

Key capabilities include:

• Zero configuration by default – no need to annotate routes or write adapter code.
• Dynamic BaseURL resolution for proxy environments, enabling per‑user or per‑deployment endpoints.
• Selective exposure through operation IDs or tags, so only the desired subset of routes is exposed to AI clients.
• Parameter preservation that mirrors Gin’s path and query parameters in the MCP tool signature, ensuring accurate request construction by assistants.
• Flexible deployment – mount the MCP server within the same application or expose it as a separate service.

Real‑world use cases span from internal tooling where developers want AI assistants to invoke API calls while writing code, to customer‑facing services that expose a friendly conversational interface for querying data or triggering workflows. For example, a SaaS product can let users ask natural‑language questions like “Show me the last 10 orders for user 42” and have an assistant translate that into a properly authenticated request. Because Gin‑MCP handles routing, schema generation, and authentication plumbing automatically, teams can focus on business logic rather than integration overhead.

In short, Gin‑MCP turns a conventional Gin API into an MCP‑ready service with minimal friction, unlocking powerful AI‑driven interactions while preserving the developer experience and performance that Gin is known for.