# Tool integration

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

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.

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

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 call math tools. Finally, it guides you on how to deploy to Cloudflare and access it remotely.

An MCP server project based on the SWAPI Star Wars API, providing query functions for Star Wars character, planet, movie, etc. data, supporting automatic pagination and cache management, and can be integrated with tools such as VS Code.

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 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 integrating the Claude desktop client into the MCP service for math tool calls. Finally, it provides a complete process for deploying to Cloudflare and remote connection.

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 demonstrates how to use FastMCP to implement a Multi - Channel Protocol (MCP) server, including tool registration, server/client usage examples, and integration with Claude Desktop and the MCP Inspector.

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.

Gin-MCP is a zero-configuration Gin to MCP bridge library that automatically exposes existing Gin API endpoints as MCP tools for instant integration with MCP-compatible clients.

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.

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.

This project is a collection of reference implementations for the Model Context Protocol (MCP), including MCP server implementations for various tools and services, aiming to provide secure and controllable access to tools and data sources for large language models (LLMs).

A web - based dialogue agent based on multiple large language models (such as Google Gemini, Anthropic Claude, etc.), which implements multi - step tool execution through the Vercel AI SDK and can interact with external services (such as WhatsApp, GitHub, etc.).

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.

MCP-Bridge is a bridge connecting the OpenAI API and MCP tools, allowing developers to use MCP tools through the OpenAI API interface, supporting non-streaming and streaming chat completions, tool calls, and other functions.

The model context protocol server for GoReleaser, providing configuration verification, deprecation repair, and documentation access functions to help AI assistants understand and operate GoReleaser configurations.

This is a service implementation based on the Model Context Protocol (MCP), building AI tool services through the tool capabilities provided by the Integration App platform.

AWorld is a multi - agent system framework aiming to bridge the gap between theoretical MAS capabilities and practical applications, providing a full - set solution from single - agent to multi - agent collaboration/competition. The project supports scenarios such as browser/mobile operations and GAIA benchmark testing, adopts a client - server architecture, integrates a rich toolchain, and includes performance evaluation and training functions.

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.

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.

MCP-Agg is a multi-platform aggregation API service that provides a unified interface to access tools such as GitHub and Slack, simplifying workflows and improving efficiency.

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.

The Toolhouse MCP server is an MCP protocol server built on the Toolhouse and Groq APIs, allowing MCP clients (such as the Claude desktop application) to connect and use multiple tools to enhance functionality.

This project demonstrates how to set up a remote MCP server on Cloudflare Workers, including the entire process of local development, OAuth login, connection with MCP Inspector and Claude Desktop client, and deployment to Cloudflare.