"Exploring GraphRAG and HybridRAG" matching MCP servers:

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

A generic MCP server that dynamically exposes any OpenAPI-documented REST API to LLMs by auto-discovering endpoints. It provides tools for exploring API capabilities and making authenticated requests directly through natural language interfaces.

An MCP server that provides tools for exploring large OpenAPI schemas without loading entire schemas into LLM context. Perfect for discovering and analyzing endpoints, data models, and API structure efficiently.

MCP server that provides tools for exploring and testing APIs through Swagger/OpenAPI documentation.

A configurable MCP server that adapts any HTTP API into an MCP toolset with generic HTTP tools (GET, POST, PUT, DELETE) and pluggable authentication. Includes API discovery scripts and supports dynamic tool generation from OpenAPI specs or wordlist scans.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

Integrate Claude with Any OpenAI SDK Compatible Chat Completion API - OpenAI, Perplexity, Groq, xAI, PyroPrompts and more.

A Python-based MCP server that integrates OpenAPI-described REST APIs into MCP workflows, enabling dynamic exposure of API endpoints as MCP tools.

Exposes add, subtract, multiply, and divide tools for performing arithmetic operations over stdio via the Model Context Protocol.

Exposes FastAPI routes as MCP tools with auto-discovery, Pydantic schema extraction, and built-in observability.

MCP server for loading and exploring OpenAPI/Swagger specifications, enabling AI assistants to dynamically browse API contracts by loading specs, searching endpoints, inspecting schemas, and retrieving operations.

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.

Enables AI assistants to interact with the Thrive MCP REST API for exploring endpoints, making test requests, and integrating with the API.

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.

Enables AI assistants to interact with the Scorecard REST API for exploring endpoints, making test requests, and integrating the SDK into applications.

Enables AI to interact with multiple Swagger/OpenAPI specifications by listing endpoints, exploring models, and generating TypeScript code. It centralizes the management of various APIs through a configuration file, allowing for seamless integration of documentation into AI workflows.

Introspects a Django REST API's OpenAPI schema and exposes each endpoint as an MCP tool, enabling Claude or any MCP client to interact with the API via natural language.

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.

A utility tool that analyzes Next.js application routes and provides detailed information about API paths, HTTP methods, parameters, status codes, and request/response schemas.

A Model Context Protocol server that enables LLMs to interact with GraphQL APIs by providing schema introspection and query execution capabilities.