OpenApi MCP Server

Open API MCP – Turning REST APIs into AI‑Ready Toolsets

Open API MCP is a specialized Model Context Protocol (MCP) server that automatically turns any OpenAPI specification into an AI‑friendly interface. By parsing the API schema, it generates a collection of strongly‑typed tools that can be invoked by an AI assistant. The server exposes these tools over a standard HTTP stream, enabling Claude or other assistants to call the underlying REST endpoints as if they were native functions. This eliminates the need for manual wrapper code, reduces runtime errors, and keeps type safety intact.

The core problem this server solves is the friction between AI assistants and legacy or third‑party APIs. Developers normally have to write custom clients, manage authentication, and translate JSON payloads into the assistant’s input format. Open API MCP removes that boilerplate by automating client generation with Zod, a TypeScript schema library. The result is a ready‑to‑use MCP that validates inputs and outputs against the OpenAPI contract, ensuring that every tool call respects the API’s expectations. For teams working with multiple services—e.g., e‑commerce, CRM, or cloud infrastructure—this means a single configuration file can expose dozens of tools with zero manual coding.

Key capabilities include:

• Automatic MCP generation from JSON or YAML OpenAPI specs, with minimal configuration.
• Zod‑based type safety, guaranteeing that request and response shapes match the API definition.
• Flexible deployment via environment variables or Docker Compose, making it easy to run locally or in CI/CD pipelines.
• Support for common authentication patterns (API keys, bearer tokens) through Axios integration.
• Streamable HTTP transport, allowing the server to participate in long‑running conversations without blocking.

Typical use cases span from building conversational bots that manage inventory or user accounts to integrating SaaS services into a single AI workflow. For example, an assistant could fetch product data, add items to a cart, and place orders—all through MCP calls that are automatically validated against the vendor’s OpenAPI schema. In a data‑science setting, the server can expose analytics endpoints, letting an AI help analysts run queries and interpret results without writing raw HTTP code.

Because the server is driven by a declarative OpenAPI file, adding or updating an API endpoint requires only re‑running the generation step. This “spec‑first” approach keeps the MCP in sync with backend changes, reduces maintenance overhead, and ensures that AI developers always interact with the most current API surface. Overall, Open API MCP bridges the gap between structured REST services and conversational AI, delivering a rapid, type‑safe, and scalable integration path.