# Tool Integration

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 mathematical tools. Finally, it provides a complete process for deployment to Cloudflare and remote connection.

This project is a list of MCP servers, covering multiple fields such as browser automation, tool integration, system automation, AI services, search, commands, workflow automation, social media, communication, customer data platforms, databases, knowledge storage, development tools, file systems, cloud storage, finance, location services, monitoring, research data, security, travel, data visualization, notes, marketing, identity, etc.

This project demonstrates how to use the MCP protocol to interact with OpenAI, Azure OpenAI, and GitHub models in Azure container applications. It provides a simple terminal application demonstration to interact with the to - do item agent through the toolset provided by the MCP server.

The Ultimate MCP Server is an AI agent operating system based on the Model Context Protocol (MCP), offering dozens of powerful tool capabilities, including cognitive enhancement, tool usage, and intelligent orchestration. The system exposes functions through standardized MCP tools, enabling advanced AI agents to access a rich tool ecosystem and specialized services while optimizing costs, performance, and quality.

Flutter Inspector is an MCP server that connects Flutter applications with AI programming assistants, providing functions for debugging and inspecting Flutter applications.

A remote MCP server project based on Cloudflare Workers, supporting OAuth login and integrable with MCP Checker and Claude desktop applications.

The Perplexity MCP Server is a Node.js - based server that implements Anthropic's Model Context Protocol (MCP) to connect Claude with Perplexity's language models and provides enhanced AI interaction tools. It supports two main tools: advanced chat completion and a simplified single - query interface.

JEBMCP is a project that combines JEB and MCP tools, aiming to simplify reverse engineering tasks through Python scripts and provide efficient code analysis and operation functions.

This project is a collection of reference implementations of 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 modular server that implements the Model Context Protocol standard, providing integration of multiple tools and unified gateway access.

An MCP server implementation based on .NET 9.0, providing communication protocols and tool integration for model-driven systems.

The Model Context Protocol (MCP) is a standardized protocol introduced by Anthropic for the interaction between large language models (LLMs) and external tools and functions, as well as for injecting context into LLMs. It enables models to request real-time information, perform operations in external systems, access professional knowledge bases, and interact with APIs and services. The MCP is similar to a USB hub, serving as a standard interface that reduces the risk of API changes because each MCP server is maintained by its own company, and users only need to integrate it. The MCP server provides three functions: tools, resources, and prompts.

A TypeScript project integrating Langchain and MCP tools, supporting interaction with language models through a chat interface and execution of various tools.

A horizontally scalable implementation of the MCP server

Documentation for the integration of the Unreal Engine Model Context Protocol (MCP), helping to understand, set up, and use the MCP system.

The Gentoro MCP server provides interaction capabilities between AI agents such as Claude and the Gentoro bridge service, supporting tool integration and function control.

The Model Context Protocol (MCP) is an open-source protocol designed to enable Large Language Models (LLMs) to seamlessly interact with external tools, services, and data sources through a standardized interface, simplifying the integration process and expanding AI capabilities.

MCP Ahrefs is an MCP server project based on the SAAGA framework, providing tool integration, exception handling, logging, and parallel processing functions, and supporting interactive testing through clients such as Claude.

The Kali MCP Server is an AI-driven network security testing platform that integrates over 55 professional security tools and supports multiple AI interfaces for intelligent penetration testing and vulnerability discovery.

This project implements a full-stack AI agent system inspired by the model context protocol, including a React front-end and a FastAPI back-end. The back-end serves as an AI coordinator, using Google Gemini to parse natural language instructions, safely call the file system, browser, or GitHub tools to perform tasks, and return the structured results to the front-end. The system focuses on software development scenarios, providing secure sandbox file operations, real-time web browsing, and repository inspection functions, and visualizing the tool call process.

This is an example project that implements the MCP application extension specification, allowing the invocation of interactive HTML/JS user interfaces through MCP tools, including server - side and client - side demonstrations.

A remote MCP server project based on Cloudflare Workers, supporting OAuth login and integrating with MCP Inspector and Claude desktop applications.

The MCP Protocol SDK implemented in TypeScript for building standardized services interacting with LLMs

An example project of building an MCP server based on Spring AI

Demonstration project for Claude desktop client configuration and tool integration

The MCP server is a service for processing the model context protocol. It supports installation through npm, yarn, or pnpm and provides examples of client calls.

MCP is an open-source AI-driven penetration testing framework that integrates multiple security tools, analyzes their outputs in real-time, strictly follows the standard penetration testing process, and provides intelligent assistance to security testers.

The Ultimate MCP Server is an AI agent operating system based on the Model Context Protocol (MCP), providing dozens of powerful tool capabilities, including intelligent task delegation, document processing, browser automation, Excel operations, etc. It achieves cognitive enhancement and complex task orchestration of AI agents through standardized MCP tools.

A modular server implementing the Model Context Protocol standard, providing integration of multiple tools such as GitHub, GitLab, Google Maps, memory storage, and Puppeteer web automation.

A local server project based on the MCP protocol, supporting custom tool integration