# AI tools

An MCP server that transforms Cloudinary API functions into callable tools for AI assistants

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement OAuth login functionality. It provides a local development guide, a method for connecting with the MCP Inspector, a solution for integrating with the Claude desktop client, and a complete process for deploying to Cloudflare.

This is an MCP server that connects to the Coreflux MQTT broker, providing Coreflux and MQTT operation tools for AI assistants such as Claude.

A production-ready MCP server template for hosting custom AI tools and prompt templates, supporting remote deployment and local operation, helping developers quickly build AI model interaction tools.

The RISKEN MCP server is a protocol server that provides RISKEN API integration, supporting automated data acquisition, scanning, and analysis, as well as building AI tool applications.

The X (Twitter) MCP server is a protocol server for interacting with Twitter through AI tools, supporting functions such as getting tweets, posting tweets, searching on Twitter, and managing followers. It uses Twitter API v2 for secure authentication.

This project implements a Telegram message sending service based on the MCP protocol, allowing AI assistants to send Telegram messages through the local service.

BrowserTools MCP is a powerful browser monitoring and interaction tool that enables AI applications to capture and analyze browser data through a Chrome extension, supporting multiple audit and debugging functions.

An MCP server based on ClickSend that allows AI assistants such as Claude to send SMS and MMS via API.

This project demonstrates a disk usage query service based on the MCP protocol, allowing Claude AI to obtain real-time disk information of a Mac system through a local server and present it in a structured and user-friendly manner.

Kontxt MCP Server is a codebase context analysis service based on the Gemini model, providing codebase understanding tools for AI clients and supporting multiple transport protocols and context attachment functions.

MCP Palette is a desktop application for managing Model Context Protocol server configurations, providing a centralized interface to configure, manage, and deploy MCP servers for large language models.

A modular server based on FastAPI and FastMCP, integrating mathematical tools, weather APIs, web searches, audio generation, and external API calls, supporting AI tool calls and resource routing.

An MCP (Model Context Protocol) server and client project based on FastMCP and LangChain, including installation dependencies and operation guides.

An MCP server that connects AI assistants with Go language analysis tools

Firecrawl MCP is a model context server extension for the Zed AI Agent, supporting the configuration of the Firecrawl service through an API key and integration into the Zed assistant mode.

The OpenAPITools SDK is a multi - AI platform tool management library that provides a unified interface to support the integration and execution of tools for models such as Claude, GPT, and LangChain, and supports both local and API usage modes.

A lightweight MCP server that retrieves relevant documentation content from popular AI libraries such as LangChain, LlamaIndex, and OpenAI by combining web search and content parsing, providing language models with the function of dynamically querying the latest documentation.

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. The project includes implementations of various functional servers, covering areas such as file systems, databases, search, and API integration, and supports development with TypeScript and Python SDKs.

A web content acquisition and processing tool based on the MCP protocol

This is a simple PostgreSQL MCP server template project designed to help developers quickly build their own MCP servers. The project provides tools, resources, and prompt templates for interacting with the PostgreSQL database, supporting querying database content through natural language.

The YouTube MCP Server is a tool for obtaining and extracting subtitles from YouTube videos, enabling AI language models to access and process video content.

MCP2Lambda is an MCP protocol server that runs AWS Lambda functions as tools for large language models (LLMs). AI models can call Lambda functions to access private resources and AWS services without code modification.

An MCP server supporting Agent8 SDK development, providing various game development tools and resource search functions

Steel MCP Server is a server based on the Model Context Protocol. Through the integration of the Puppeteer tool and the Steel browser, it enables LLM models like Claude to perform automated operations such as web page navigation, clicking, and input. It supports both local and cloud running modes and provides web page interaction and screenshot functions.

This project demonstrates how to build a remote MCP server on Cloudflare Workers, including the OAuth login function, and supports connection and use through the MCP Inspector and Claude desktop client.

This project studies the MCP server deployment scheme used by the research team, including local development configuration and Kubernetes containerization deployment, and explores how to implement team - shared AI tool services.

The API-MARKET MCP Server is a model context protocol server that exposes over 200 API endpoints of API-Market as MCP resources, enabling large language models to discover and interact with these APIs through the MCP protocol.

Awesome - MCP - ZH is a collection of MCP (Model Context Protocol) resources tailored for Chinese users, including basic introductions, usage guides, client, server, and community resources to help users quickly get started with MCP.

FastMCP is a TypeScript-based framework for building MCP servers that support client sessions. It provides simple definitions for tools, resources, and prompts, supports functions such as authentication, session management, returning image and audio content, logging, error handling, SSE communication, etc., and includes CLI tools for testing and debugging.