# Tool integration

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.

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 scenarios such as integrating the Claude desktop application to call mathematical tools. Finally, it can be deployed to the Cloudflare cloud service.

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.

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.

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.

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 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.

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.

A proof - of - concept project for a server implementing the Model Context Protocol (MCP), providing custom tools and resources to enhance the capabilities of AI assistants, including document search, web page crawling, and Google Search API integration.

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.

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.

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.

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 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.

This project is a collection of Model Context Protocol (MCP) servers, including service implementations with various functions such as calculators, weather queries, and file management, providing standardized tool access interfaces for MCP clients.

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.

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.

The MCP portal is the official community platform for the Model Context Protocol, providing resources such as documentation, practical guides, server implementations, and tool integrations. It supports AI models to access external tools through the MCP protocol, covering a wide range of scenarios from database connections to multimodal applications.

This project is a Python-based MCP server for integrating custom tools in AI-assisted development environments, providing addition operations and API key retrieval functions.

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 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).

The project introduces the advantages of the MCP architecture in AI applications. By comparing single-server and multi-server clients, it shows how to efficiently connect mathematical and weather services and use the LangGraph ReAct agent for intelligent calculations.

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.

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.

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.

Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-developed servers, enabling large language models (LLMs) to securely and controllably access tools and data sources. The project includes various types of server implementations covering multiple domains such as file systems, databases, Git, and Slack, demonstrating the diversity and scalability of MCP.

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.