# Tool integration

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement the OAuth login function. It supports local development and debugging, connection testing through MCP Inspector, and integration into the Claude desktop application for using mathematical tools.

This project demonstrates how to set up a remote MCP server on Cloudflare Workers, including OAuth login functionality, supporting local development and cloud deployment, and enabling integration with the MCP inspector and the Claude desktop application.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement the OAuth login function. It supports local development and debugging, connection testing through the MCP Inspector, and integration into the Claude desktop application to invoke mathematical tools. Finally, it also provides a complete process for deploying to Cloudflare.

An MCP server project based on TypeScript, supporting custom tools and integration with hosts such as Cline

This project provides a series of Model Context Protocol (MCP) servers for enhancing the external capabilities of AI assistants, including independent implementation modules for specific functions such as educational course queries.

This project demonstrates how to set up a remote MCP server on Cloudflare Workers and implement OAuth login functionality. It provides a complete process for local development, MCP Inspector connection, Claude desktop application integration, and deployment to Cloudflare.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement the OAuth login function. It supports local development and debugging, connection and testing through the MCP inspector, and integration into the Claude desktop application to call mathematical tools. Finally, it also provides a complete process for deploying to Cloudflare and remote connection.

The MCP startup project is an AI application development framework that includes a Python server - side and a TypeScript client - side, supporting the interaction between AI models and external tools/APIs, and providing functions such as document search and conversation management.

MCP Mediator is a Java - based implementation of the Model Context Protocol (MCP) mediator, providing seamless integration between MCP clients and servers, supporting efficient communication and tool execution. The project includes core modules, examples, and various service integrations, supports quickly converting existing code into MCP services through annotations, and has the ability to proxy multiple servers.

This project is a remote Model Context Protocol (MCP) server based on Node.js and TypeScript, deployed in Azure Container Apps, used to implement standardized communication between AI models and tools. It provides a quick start guide, supports local development, GitHub Codespaces, and Azure deployment, and includes SSE protocol implementation, SQLite database integration, and tool interaction features.

The MCP LLM Bridge is a bridging tool that connects the Model Context Protocol (MCP) server with OpenAI-compatible LLMs. It enables bidirectional protocol conversion between MCP and the OpenAI function call interface, supporting both cloud and local model calls.

The Gentoro MCP server supports the Gentoro service, enabling Claude to interact with the Gentoro bridge and its underlying functions. Users can create and manage tool bridges through their Gentoro accounts and integrate them into agents such as Claude via API keys.

A lightweight MCP server implementation that exposes custom tools via SSE for AI client integration.

This project is a FastMCP server that provides batch file and folder operation tools, including file reading and writing, creation, moving, deletion, and other operations. It supports batch calls to tools to improve efficiency.

ToolChat is a tool for interacting with large language models (LLMs) via MCP servers, supporting the configuration of multiple tool servers and the invocation of specific functions, and can also handle multimodal input such as images and documents.

A guide to converting a Robot Framework library into an MCP server. By adding specific functions and configurations, the library can run as an MCP service for client calls.

AI-based image explanation generation service

StatusNow.Dev provides a comprehensive website and server monitoring solution, including SSL/domain expiration monitoring, website availability, response time, etc.

click-mcp is a Python library that extends Click applications through Model Context Protocol (MCP) support, enabling AI agents to interact with CLI tools.

The Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers. It aims to provide large language models (LLMs) with secure and controllable access to tools and data sources. These servers demonstrate the diversity and scalability of MCP, covering various functions from file system operations to database integration, from web search to AI image generation.

The Agentic MCP Client is an independent AI agent runner that interacts with models such as Claude, BedRock, and OpenAI through MCP protocol tools, supporting autonomous cloud operation and secure system interaction.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement the OAuth login function, supporting connection and use through the MCP Inspector and Claude Desktop clients.

Glasses MCP is a tool that provides web page visual capabilities for AI assistants, allowing AI to obtain visual information of web pages through screenshots, supporting multiple devices and formats.

This project includes the Cloud Security Alliance model context protocol servers, covering various functional modules and service interfaces, including multiple useful tools imported from Anthropic and chat services provided by CSA.

GhidrAssistMCP is a powerful Ghidra extension that enables AI assistants and other tools to interact with Ghidra's reverse engineering capabilities through a standardized API by implementing a Model Context Protocol (MCP) server.

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers and implement OAuth login functionality. It supports local development and debugging, connection testing through the MCP Inspector, and integration into the Claude desktop application to call math tools. Finally, it provides a complete process for deploying to Cloudflare and remote connection.

This project demonstrates how to integrate OpenAI, Azure OpenAI, and GitHub models through the MCP protocol to build a terminal application for a TODO list agent. The project includes three major components: MCP host, client, and server, supports HTTP and SSE protocols, and provides tool invocation and database storage functions.

mcpo-docker is a Docker image project that provides OpenAPI-compatible HTTP endpoints for MCP (Model Context Protocol) servers, facilitating integration with OpenWebUI.

An AI agent application based on Spring Boot and Spring AI, helping users book accommodation in tourist cities, supporting multiple AI models and tool integration.

mcpo is a simple and easy-to-use proxy tool that can quickly convert any MCP tool into an OpenAPI-compatible HTTP server, enabling access through standard RESTful interfaces and facilitating integration with LLM agents and applications.