# Tool Integration

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.

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.

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 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 guides you on how to deploy to Cloudflare and access it remotely.

Portkey's Model Context Protocol (MCP) server implementation for connecting AI tools and services. Supports Docker, binary, and source code installation, provides SSE and stdio transport modes, and can be integrated with Cursor IDE and Claude Desktop.

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.

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.

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

MCP is a Python service framework that supports quickly creating local or HTTP services through tool functions and provides multiple running modes and client interaction modes.

This project provides a FastMCP server for batch execution of file and folder operations, including reading, creating, moving, deleting, etc., supporting centralized exception handling and batch tool calls.

This project demonstrates how to build a remote MCP server on Cloudflare Workers, including the OAuth login function, and supports connection and use through the MCP inspector and Claude desktop client.

This project demonstrates how to run n8n workflows in a local Docker environment, integrate an AI agent with external tools (such as web search) through the Model Context Protocol (MCP), and use npx to dynamically start the MCP service to achieve dynamic discovery and use of tools.

The Letta MCP Server is a server toolset that provides agent management, memory operations, and Letta system integration.

This project showcases an MCP server and client built with Rust, communicating via SSE and integrating a simple addition tool. The project includes the complete process of MCP server setup, tool registration, integration with the RIG agent, and interaction through the MCP inspector.

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, a complete process for deploying to Cloudflare is provided.

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

This project demonstrates how to use the Model Context Protocol (MCP) to integrate local and remote tools in the AutoGen framework, including a local mathematical calculation server and a remote Apify web browsing tool. It enables flexible interaction between AI agents and tools through a standardized protocol.

Voxta MCP Bridge Provider, enabling communication between Voxta and MCP protocol servers, supporting feature expansion through external tools.

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.

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.

MCP Servers Schemas is a project that provides various MCP server definitions. Users can quickly obtain the latest server information and tool definitions without local installation.

This project demonstrates an example implementation of the Model Context Protocol (MCP), which is a standardized protocol for enhancing the capabilities of AI assistants and extending their functionality through custom tools and data sources. The project includes multiple MCP server examples, such as task managers, file explorers, and weather services, and provides guidelines on how to set up and use these servers.

Cline's MCP protocol backend service, providing knowledge base integration and retrieval functions

This project is a setup guide for a Claude - compatible MCP server based on Python and FastMCP, supporting Windows and macOS/Linux systems, providing tool and resource management functions.

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.

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

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.

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

Ultra-MCP-Servers is an open-source project that enables users to create and manage their own Model Context Protocol (MCP) servers. It offers a variety of tool and service integrations, such as YouTube transcription, cloud storage, web crawlers, etc., and encourages community contributions.