"Creating an MCP Server" matching MCP servers:

An MCP server for interacting with Treasure Data API, allowing users to retrieve database information and check server status through natural language queries.

⚙️ A Model Context Protocol (MCP) that provides tools for fetching and creating Reddit content

A TypeScript-based MCP server that provides backend API handling and facilitates communication between microservices. Features an organized structure with controllers, routes, and models for easy extensibility and maintenance.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

An MCP protocol server that provides access to supOS open APIs, allowing MCP-compatible clients to query topic tree structures and details.

An MCP server that provides AI agents and LLMs with standardized tool access to the ICON MCP v109 API. It supports asynchronous operations and simplifies deployment through Docker and Docker Compose.

Instantly converts any running FastAPI application into an MCP server by parsing its OpenAPI spec, enabling Claude to call all endpoints via natural language without manual tool writing.

An MCP server that enables AI agents and LLMs to interact with the Test MCP Server Feb6 USDT API through standardized tools. It provides features such as Docker support and async operations for efficient integration.

Dynamically creates an MCP server from any OpenAPI schema, enabling seamless integration with tools like Prompteus and Claude.

An MCP server that provides access to the Test MCP Feb 5 API, enabling AI agents to interact with its endpoints through standardized tools. It supports seamless AI integration via the Model Context Protocol and is designed for easy deployment using Docker or Google Cloud Run.

An MCP server that enables AI agents to interact with the Test MCP Mar19 USDC API through standardized tools. It supports seamless integration via the Model Context Protocol and features Docker-ready deployment.

Enables LLMs to make HTTP requests using structured cURL commands with support for multiple authentication methods, custom headers, and comprehensive request/response control.

Enables AI agents to connect to any GraphQL endpoint, introspect schemas, and execute queries or mutations through auto-generated tools.

Parses Swagger 2.0 and OpenAPI 3.x specifications, exposing API endpoints, schemas, and authentication through MCP tools with local caching to reduce token usage.

Enables load testing and validation of an order API by generating synthetic orders, previewing them, and sending batches while enforcing guardrails like bounded counts and fixed seeds for replay.

MCP server that exposes RESTForge capabilities to AI agents, enabling them to set up, configure, generate code, and manage RESTForge projects through natural language.

Validates OpenAPI specs from files, inline content, or URLs, and generates prompts for agent developers based on the API analysis.

Enables AI assistants to explore and interact with the Facets Control Plane API via natural language, supporting operations like searching endpoints, loading schemas, and making authenticated API calls.

MCP server for reading, writing, and organizing API documentation in Apidog.

A read-only API change deploy gate for AI coding agents that analyzes OpenAPI specs to determine if changes are safe to deploy. It provides tools for comparing specs, explaining breaking changes, and generating migration guides.