"Setting up Minecraft (MCP) servers with Python and Visual Studio Code" matching MCP servers:

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.

Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.

Enables AI agents to create, edit, read, and run Bruno API collections (both .bru and .yml formats) with byte-parity to Bruno's own reader, without requiring the Bruno CLI.

An MCP server that demonstrates converting a safe OpenAPI subset into MCP tools and interactive apps, using the GitHub API as an example. It provides three GitHub tools with summary, table, and ranking views.

Enables AI agents to securely list, retrieve, and search Freshdesk support tickets through typed read-only MCP tools. It supports API-key authentication, rate-limit handling, safe logging, and an offline fictional demo mode.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

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

Enables LLMs to discover and use generated REST API services as Model Context Protocol tools and resources, supporting CRUD actions and read-only data access without custom glue code.

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.

An open standard server implementation that enables AI assistants to directly access APIs and services through Model Context Protocol, built using Cloudflare Workers for scalability.

A Python server implementing the Model Context Protocol that exposes tools for querying external APIs, compatible with Claude Desktop and ChatGPT Desktop.

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.

Enables reading and searching API documentation from YApi instances, allowing AI models to access interface definitions, project API lists, and search through API endpoints using YApi URLs or project IDs.

TrustPilot for APIs, built for AI agents. Independent reliability ratings for APIs and MCP servers — look up trust scores, compare providers side by side, and leave reviews from real agent traffic.

Optimizes REST API calls for AI agents by returning compact schemas instead of full responses, allowing agents to fetch only needed fields via jq masks, reducing token consumption by up to 50x.

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

Code Mode MCP server for the OVH API. Two tools (search + execute) give LLMs access to all OVH endpoints via sandboxed JavaScript.

Enables AI assistants to fetch and understand API endpoint definitions from Apifox projects in real-time. Supports retrieving complete API specifications including request methods, parameters, headers, and response schemas to improve development efficiency and code generation quality.

Enables MCP hosts to list, look up, and describe a static catalog of OpenAPI operations, and to inspect a governing contract and explicit deny-list that define what the server refuses to do.

Provides AI-enabled access to Amazon Business API documentation, sample code, and troubleshooting resources. Enables developers to search and retrieve API documentation, generate integration code, and get guided solutions for common errors during the API integration process.