"Using Git with Python for Operations" matching MCP servers:

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

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

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.

Enables AI assistants to interact with the Post For Me API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

MCP server for Akamai APIs. 198 tools covering Property Manager, Edge DNS, CPS, WAF, and reporting. Built with TypeScript, featuring modular architecture, comprehensive testing, and multi-account support. Make Akamai accessible to AI assistants.

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.

Enables natural language interaction with FastAPI applications through Google's Gemini AI using MCP tools. Provides CRUD operations for user management and application health monitoring through conversational prompts.

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

Free x402 endpoint checker plus paid report and metadata tools. Remote MCP server for agents. Written by AI named Nock, not a human.

This server enables interacting with the National Digital Health Mission's Health Information User (HIU) API, allowing agents to access and manage health information through the Multi-Agent Conversation Protocol.

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

MCP server for scraping with declarative configs

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.

Enables AI agents to create, run, and manage HTTP requests using the Invoker API client's .ivk format. It provides tools for scanning collections, executing requests, managing environments, and building documentation sites.

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

An MCP server that provides tools to interact with the JSONPlaceholder fake REST API for testing and prototyping, supporting CRUD operations on posts, comments, todos, and users.

Self-healing API proxy MCP that sends REST requests, diagnoses failures using Claude, patches requests, and retries. Successful fixes are remembered for instant reuse.

Exposes YApi's API management capabilities to MCP clients, enabling operations like listing projects, categories, searching APIs, and managing API details.

Enables local analysis of OpenAPI 3 and Swagger 2 JSON/YAML spec files on disk, with no remote fetching of specs or credentials. It groups endpoints by tag, flags operations that appear to lack security, lists deprecated operations, and produces short markdown cheat sheets for agents.