mcp-openapi-schema-explorer and openapi-to-mcp
One tool provides token-efficient access to OpenAPI/Swagger specs for client-side exploration using MCP Resource Templates, while the other generates individual MCP servers for each endpoint within an OpenAPI/Swagger API, enabling AI clients to interact with REST APIs via Streamable HTTP.
About mcp-openapi-schema-explorer
kadykov/mcp-openapi-schema-explorer
MCP server providing token-efficient access to OpenAPI/Swagger specs via MCP Resource Templates for client-side exploration.
This tool helps developers or AI agents understand complex API documentation (OpenAPI/Swagger specifications) without needing to load the entire document. It takes a local file path or remote URL to an OpenAPI or Swagger specification as input and allows an MCP client to explore specific parts of the API structure on demand. The output is structured information about the API, tailored for developers building against APIs or AI assistants interacting with them.
About openapi-to-mcp
EvilFreelancer/openapi-to-mcp
Turns any OpenAPI/Swagger API into an MCP server. One MCP tool per endpoint, Streamable HTTP - for AI clients calling your REST API.
This project helps developers integrate their existing REST APIs with AI clients that use the Model Context Protocol (MCP). It takes an OpenAPI/Swagger specification as input and automatically generates a dedicated MCP tool for each API operation. The output is an MCP server that translates AI client requests into standard HTTP calls to your backend API, making your API accessible to AI agents without manual integration.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work