This project is a collection of learning resources about Model Context Protocol (MCP), including guides, tools, and server implementations, aiming to help developers understand and apply the MCP standard. The project provides multiple example implementations of MCP servers, such as file system operations, Git management, GitHub integration, etc., as well as development guides and practical tools.

LYRAIOS is a multi-AI agent operating system based on the Model Context Protocol (MCP), aiming to extend AI application functions by connecting financial networks and public blockchain chains, providing services such as blockchain operations, fintech analysis, and educational learning.

Pipelock is an open-source AI agent firewall that provides security protection with zero runtime dependencies through a single binary file. It adopts an architecture with separated capabilities and deploys a nine-layer scanning pipeline between the agent and the Internet to prevent secret leakage, prompt injection, and malicious tool calls. It supports multiple proxy modes (Fetch proxy, forward proxy, WebSocket proxy) and MCP proxy, and provides functions such as an emergency stop switch, audit logs, and SIEM integration.

The Allora MCP Server is an implementation based on the Model Context Protocol (MCP) that provides the function of obtaining machine learning inference data from the Allora network, enabling AI systems to seamlessly access Allora prediction market data.

The ScrapeGraph MCP Server is a production - ready model context protocol server that provides seamless integration with the ScrapeGraph AI API, enabling language models to leverage advanced AI - driven web scraping capabilities.

An interactive LeetCode MCP server that provides AI - guided authentication, learning guidance mode, code submission, and detailed feedback functions, supporting multi - language programming practice and user data tracking.

The GoHighLevel MCP server is a fundamental project aiming to connect the GoHighLevel community with AI automation through the Model Context Protocol (MCP). It provides access to all sub - account level GoHighLevel API endpoints, supports 269 tools, covering multiple functional categories such as contact management, messaging, sales pipelines, and calendar appointments. The project emphasizes community collaboration, an open architecture, and educational resources, while also reminding users to pay attention to key issues such as AI security, rate limits, and data security.

The MCP Game Helper is a custom model context protocol server that provides AI - assisted tools for game developers, focusing on tasks such as combat balance, skill analysis, level rhythm, and simulation.

This is a server based on the Model Context Protocol (MCP) that allows AI assistants to control the Unreal Engine game engine through the remote control API, enabling game development automation. It supports various functions such as asset management, actor control, editor operations, level management, animation physics, visual effects, and Sequencer control.

The ConsultingAgents MCP Server is a multi - model consulting agent server that provides four AI expert consulting services (Darren, Sonny, Sergey, Gemma) for Claude Code through the MCP protocol, supporting code analysis, document search, and repository - level development planning.

The MCP server automatically routes design tasks to the currently best design model on the designarena.ai leaderboard via OpenRouter, enabling dynamic selection of the optimal AI for design work.

A server that provides Model Context Protocol (MCP) services for LeetCode, supporting AI assistants to access LeetCode problems, user information, and contest data.

This project guides developers on how to integrate the MCP service with GitHub Copilot to extend the capabilities of the AI-assisted development workflow. Through less than an hour of learning, users will set up the GitHub MCP server, implement Copilot proxy mode integration, and complete the full process practice from issue research to code submission.

The OP.GG MCP Server is a server that implements the Model Context Protocol, providing a standardized interface for AI agents to access OP.GG game data and supporting data query functions for multiple games such as League of Legends and Valorant.

The XRPL MCP Server is a bridge connecting AI models with the XRP Ledger, providing a standardized API interface to access ledger data.

An XRP Ledger service server based on the Model Context Protocol (MCP), providing a unified interface for AI agents to interact with the XRPL MainNet, TestNet, and DevNet, supporting various blockchain services such as account management, token operations, NFT functions, DID, and AMM.

An enterprise - level AI assistant system based on the Model Context Protocol, with intelligent server selection, text analysis, code review, sentiment analysis, and knowledge management functions, providing an aesthetically pleasing Web interface.

GUARDRAIL is a security framework specifically designed for the large language model (LLM) application ecosystem, providing comprehensive protection especially for the Model Context Protocol (MCP). It uses a multi - layer architecture, including an information gateway layer, a context verification layer, a request control layer, an execution isolation layer, and an audit monitoring layer, aiming to prevent data leakage, unauthorized access, and resource abuse. This framework emphasizes progressive adoption, allowing developers to gradually enhance security while maintaining high performance and ease of use.

MCP Serve is a powerful deep learning model server tool that supports deployment through Shell execution, Ngrok connection, or Docker containers, and integrates multiple advanced AI technologies.

Awesome MCP FastAPI is an enhanced Model Context Protocol (MCP) service implemented based on the FastAPI framework. It provides powerful tool registration functionality and automatic documentation generation, leveraging the mature FastAPI ecosystem to achieve high-performance AI tool integration.

An AI research assistant tool based on Node.js and the Gemini API. It uses Firecrawl for web data scraping, leverages the Gemini large - model for in - depth language understanding and report generation, supports iterative in - depth research, and can be integrated with the MCP protocol.

Createve.AI Nexus is an open - source project that bridges the gap between AI agents and enterprise systems by implementing the Model Context Protocol (MCP) standard. It provides secure, real - time data access and system integration capabilities. It supports multiple AI platforms, has an enterprise - level security architecture, and can connect various business applications, sensor data, and document management systems.

The EspoCRM MCP Server is a comprehensive model context protocol server that provides seamless integration with EspoCRM, supporting 47 tools for complete CRM operations, including contact, account, opportunity, meeting, user, task, lead management, and advanced functions such as team, role, and entity relationship management, along with an AI chatbot interface.

Vulcan File Ops is a high - performance file operation server based on the Model Context Protocol (MCP) that can transform desktop AI assistants (such as Claude Desktop, ChatGPT Desktop, etc.) into powerful development partners. It provides secure file reading and writing, batch operations, document processing, image analysis, and Shell command execution functions. It features enterprise - level security controls, dynamic directory registration, and intelligent tool filtering, allowing users to have full control over local file system access.

Personal learning project aiming to understand protocol design, client - server communication, and modular architecture through implementing a module protocol server.

The AIStor MCP server is a service based on the Model Context Protocol (MCP) for interacting with AIStor object storage. It supports various operations, including reading, writing, deleting, and management functions, such as listing buckets and objects, getting metadata, creating presigned URLs, and using AI to describe object content. It has flexible configuration and can enable operations at different permission levels through flags.

MySQL MCP Server is a service component that implements the Model Context Protocol (MCP), providing a secure and structured interaction interface between AI applications and MySQL databases. It supports functions such as listing database tables, reading table content, and executing SQL queries. Database connections are configured through environment variables, emphasizing security and the principle of least privilege.

SHARP is an AI model developed by Apple Research, capable of quickly converting a single 2D photo into a 3D Gaussian Splat representation, achieving real-time conversion from photos to interactive 3D scenes, with an inference time of less than one second.

Skim MCP Server is a production - level Model Context Protocol server based on the Skim project. It is specifically used for intelligent code compression to help AI assistants like Claude Code break through the context length limit and analyze large code projects.

This is a Python - based custom MCP (Model Context Protocol) server demonstration project, aiming to show how to build a server that uses a custom protocol for communication. It is suitable for learning network programming and protocol design.

The Integrator MCP Server is a legacy model context protocol server that can convert Integrator automated workflows into tools that can be called by AI assistants, enabling two-way interaction.

This project uses advanced AI prompting techniques to enable an AI agent (based on Google Gemini model) to interact with the legacy Windows application MSPaint through the Model Context Protocol (MCP) to solve complex math problems and draw solutions on the canvas.

Lex is a TypeScript framework that provides situational memory and architecture awareness for AI agents, solving the problem of context loss in long - process development. Through memory snapshots, module dependency navigation, and architecture policy execution, it enables AI assistants to remember work progress and understand code structure.

MetaVault MCP is a cross - protocol yield intelligent service designed for AI agents, providing unified access to three major protocols: Spectra Finance, Pendle, and Morpho through the Model Context Protocol (MCP). It offers 50 read - only tools, covers more than 10 blockchains, and supports functions such as fixed - rate discovery, portfolio analysis, leveraged looping strategy calculation, yield curve analysis, historical on - chain data query, and cross - protocol comparison. Its core architecture uses an 'open - emergence' design. Through three - layer knowledge transfer (protocol principles, tool description, structured output prompts) and observation coverage quantification, AI agents can independently discover novel strategies without understanding the underlying mechanisms, avoiding premature pattern matching and narrative solidification.

A multi-functional AI agent project that includes an Arabic legal chatbot, a Google search tool, and a handwritten digit generation model.

Leonardo MCP Server is a model context protocol server supporting HTTP and stdio modes, used to interact with Leonardo AI and support functions such as creating image generation tasks and viewing model status.

This project implements a CRM - AI service middle layer based on the MCP protocol, providing data security processing, intelligent conversation management, and lead analysis functions. It protects sensitive data through anonymization technology and a token system, and supports integration with large - language models.

An MCP server that integrates the Perplexity AI search - enhanced language model with the Claude desktop, providing three tools of different complexity levels, suitable for quick queries, technical analysis, and in - depth research scenarios.

MCP Sigmund is a financial data analysis and learning tool based on a PostgreSQL database. It provides intelligent formatted financial data query services for AI assistants through the Model Context Protocol and is only for educational purposes.

This project is a GitHub repository for testing and exploring the implementation of the Model Context Protocol (MCP) server, containing sub - projects related to learning multiple programming languages, DevOps tools, game development, and AI.