# Tool Integration

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.

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.

An MCP protocol server written in Scala 3, supporting multiple tool functions.

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

A Model Context Protocol (MCP) tool for interacting with Polymarket via the Claude desktop application

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 project demonstrates how to deploy a remote MCP server on Cloudflare Workers and achieve secure access through OAuth login. It supports local development and debugging, connection with the MCP checker and the Claude desktop client, and can finally be deployed to the Cloudflare cloud.

This project is a collection of various Model Context Protocol (MCP) servers used to extend the capabilities of AI assistants, supporting the direct use of external tools and services in Claude conversations.

This project provides a configuration guide for integrating OWASP ZAP as a man-in-the-middle proxy server with SQLMap for legal security testing and vulnerability assessment. It includes quick setup scripts, manual installation instructions, advanced configuration rules, and usage examples.

Skynet - MCP is a hierarchical AI agent network project based on the Model Context Protocol (MCP), supporting the creation of sub - agents to process complex tasks in parallel, integrating multiple AI models and service tools, and providing functions such as dual - mode operation, tool discovery, and asynchronous execution.

This project provides a server and client system based on the MCP protocol for obtaining research papers from arXiv. The server processes queries and retrieves relevant papers, and the client interacts with the server through the Streamlit interface, integrating tools such as LangChain and Groq to enhance query processing capabilities.

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.

ACI.dev is an open-source AI agent tool infrastructure that provides multi-tenant authentication, permission management, and dynamic discovery functions for over 600 pre-integrated tools. It supports calls through a unified MCP Server or a lightweight SDK, simplifying the development of production-level AI agents.

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.

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).

The MCP Toolkit is a modular server implementation for building high-precision vertical AI agents, providing support for 123 tools, significantly reducing the amount of code, and simplifying complex workflows.

A TypeScript bridge project connecting local LLMs to MCP servers, providing a web interface that enables open-source models to use tool capabilities similar to Claude, supporting functions such as file system operations, web search, and complex reasoning.

A Node.js client for integrating remote MCP servers to provide tool support for Voiceflow agents, supporting multiple tool discoveries and Claude AI 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.

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

A basic MCP server project that can be integrated with tools such as Cursor to provide services like weather queries.

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.

This project includes two MCP servers: OnePiece for querying anime character information and IP address geographical location query services. It is developed using TypeScript and can be integrated with AI clients through standard input and output.

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.

Flux is an AI-based AO tool call enhancement system that enables AO code execution and custom blueprint creation through natural language, supports integration with existing AI development tools, and provides code testing functions.

An LLM service framework based on YAML configuration

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

An MCP server implementation based on Ruby 3.3, providing greeting and calculation tools, supporting Cursor integration and background operation.

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.