OpenAPI MCP Server

OpenAPI MCP turns any OpenAPI 3.x specification into a fully‑functional, AI‑friendly Model Context Protocol server in seconds. By parsing the spec and automatically generating a set of MCP tools—each corresponding to an API operation—the server removes the need for hand‑crafted adapters or custom code. Developers can immediately expose a REST service to Claude, Gemini, or any other agent that speaks MCP, allowing the assistant to discover, validate, and invoke endpoints with a single, consistent interface.

The server’s core value lies in its instant conversion workflow. A simple command validates the spec, lints for best practices, and produces a JSON schema that describes every operation’s parameters, request bodies, and responses. The resulting MCP tool set is then served over standard input/output or a lightweight HTTP endpoint, making it trivial to plug into existing development pipelines. Because the output is machine‑readable and type‑annotated, agents can parse responses reliably without custom parsing logic.

Key capabilities include comprehensive parameter handling (path, query, header, cookie, and body), built‑in authentication support for API keys, bearer tokens, Basic auth, and OAuth2, and a safety layer that prompts confirmation for destructive HTTP verbs. The server also offers an OpenAPI validation API, linting tools that surface missing s or schema errors, and optional documentation generation in Markdown or HTML. These features give developers a single tool to both expose APIs to agents and maintain high‑quality OpenAPI contracts.

In practice, OpenAPI MCP shines in scenarios such as: AI‑driven code editors that can call a backend service directly from the assistant, continuous integration pipelines where agents validate and lint API definitions before deployment, or interactive demos that let users query a live service through an AI interface. By abstracting the intricacies of HTTP and JSON, it lets developers focus on business logic while ensuring agents can interact with APIs safely and predictably.

The integration flow is straightforward: a developer runs the MCP server against an OpenAPI file, the agent receives the tool description via MCP, and then can invoke operations by sending structured JSON requests. The server’s consistent output format—complete with and fields—ensures that parsing errors are rare, making the assistant experience smooth even for complex APIs. This tight coupling between OpenAPI contracts and MCP tooling gives developers a powerful, low‑friction bridge to AI assistants.