# Tool Integration

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

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

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.

Demonstration project for Claude desktop client configuration and tool integration

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

This project provides two types of MCP servers for accessing functional tools managed by ACI.dev: the apps-server provides access to tools for specified applications, and the unified-server provides functions for discovering and executing all available 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.

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

A production-grade starter template for an MCP server based on TypeScript, providing rapid development tools and a standardized workflow.

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.

This is a Clojure SDK for creating a Model Context Protocol server, providing core components, communication processes, and example implementations, supporting tool calls, resource reading, and prompt retrieval.

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

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.

An LLM service framework based on YAML configuration

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 guides you on how to build a client-host-server system based on the MCP protocol, including a FastAPI server, an MCP client, and an SSE streaming server. It enables the interaction of resources, tools, and prompts and supports integration with the Claude desktop application.

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 the OAuth login function. It supports local development and debugging, connection testing through the MCP Inspector, and integration with the Claude desktop application to use mathematical tools.

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.

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

This project demonstrates how to deploy a remote MCP server on Cloudflare Workers, including the entire process of local development, OAuth login, connection with the MCP inspector and Claude desktop client, and final deployment to Cloudflare.

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.

An SSE-based MCP server that provides tools for querying OCI registries and container images, supporting functions such as getting image information, listing tags, and obtaining manifests and configurations.

An MCP server project integrating personal automation tools, aiming to call private tools through an AI proxy for efficient management

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.

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.

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 provides multiple Model Context Protocol (MCP) services for extending AI assistant capabilities and supports standalone installation and use.

The Gentoro MCP Server is middleware designed for Gentoro services, allowing agents such as Claude to interact with underlying functions through the Gentoro bridge, supporting dynamic integration and management of tools.