"Swagger" matching MCP servers:

A read-only MCP server for navigating OpenAPI / Swagger specifications, enabling agents to search endpoints, retrieve parameters and schemas, and inspect authentication without loading the full spec into context.

An MCP server that connects to a Swagger specification and helps an AI to build all the required models to generate a MCP server for that service.

Enables natural language exploration of OpenAPI/Swagger specs, allowing users to register APIs, browse endpoints, describe schemas, and detect breaking changes through conversational queries.

swagger-mcp is a tool designed to scrape Swagger UI by extracting the swagger.json file and dynamically generating well-defined mcp tools at runtime. These tools can be utilized by the MCP client for further tool selection.

High-performance server for exploring Swagger/OpenAPI specifications with dynamic session management, lightning-fast endpoint search, and efficient caching. Enables AI assistants to discover, search, and generate code from REST APIs.

Automatically converts Swagger/OpenAPI specifications into MCP servers, enabling AI agents to interact with any REST API through natural language by exposing endpoints as AI-friendly tools.

A stdio MCP server that caches Swagger/OpenAPI documents for multiple backend services and provides offline API search, retrieval, and request example generation. It only contacts remote servers when explicitly refreshing the cache.

Dynamically generates MCP tools from Swagger/OpenAPI specifications by extracting swagger.json files at runtime. Enables natural language interaction with any REST API that has Swagger documentation.

Enables AI agents to search and retrieve API documentation from an internal Swagger platform via MCP.

Connects AI agents with Swagger/Knife4j API documentation, enabling real-time retrieval, search, and structured understanding of API interfaces, parameters, and schemas.

Automatically generates TypeScript API code from Swagger/OpenAPI documentation. Supports listing services, tags, endpoints, and generating code by tag or endpoint.

A powerful MCP server for querying and processing large Swagger/OpenAPI JSON documents, enabling LLMs to efficiently access API documentation without loading entire files.

A TypeScript-based MCP server that integrates with Swagger/OpenAPI specifications to expose API endpoints as tools for Large Language Models (LLMs), enabling natural language interaction with any OpenAPI-compliant API.

A Swagger/OpenAPI query tool for MCP clients like Cursor, enabling AI assistants to browse, search, and retrieve detailed API type information.

Enables AI assistants to interact with Spring Boot backend APIs through Swagger/OpenAPI documentation, allowing listing, describing, and generating frontend code for endpoints.

Automatically converts Swagger 2.0 API specifications into MCP tools, enabling AI assistants to directly call REST APIs. Supports both local Swagger files and remote URLs with comprehensive parameter validation and error handling.

An MCP server that allows users to query and retrieve request and response JSON schemas directly from Swagger/OpenAPI specifications. It supports automatic reference resolution and path parameter matching to help AI models interact with API interfaces.

An MCP server that crawls and parses OpenAPI JSON or Swagger UI URLs to provide concise endpoint summaries. It enables LLMs to discover and interact with API interfaces by extracting methods, paths, and operation IDs from documentation sources.

A server based on Model Context Protocol that parses Swagger/OpenAPI documents and generates TypeScript types and API client code for different frameworks (Axios, Fetch, React Query).

Turns any SpringDoc-powered Spring Boot API into a production-ready MCP gateway, exposing existing controllers as safe MCP tools with discovery, validation, response shaping, and workflow orchestration.