A modular application demonstration based on FastMCP, integrating the MCP server, FastAPI interface, and LLM Agent functionality. It uses a modular design, supports dual operating modes, and LLM integration.

A production-level MCP server implementation that integrates Torob product search and Instagram content analysis functions. It is built on high-performance FastMCP, supports the full MCP protocol specification, and features dual-mode operation and modular design.

A modern iOS automation server based on FastMCP 2.0 and clean architecture, featuring modular design, cross - platform readiness, and cloud deployment capabilities.

A modular MCP server implementation based on LangGraph, with a clear architectural design for easy maintenance and expansion.

Distri is a Rust-based composable AI agent framework that supports building and combining intelligent agent capabilities through the MCP protocol, offering modular design and high efficiency.

The openwrt-mcp-server is a lightweight and scalable MCP protocol server designed for OpenWrt embedded devices. It supports both MQTT and HTTP protocols, enabling two-way JSON-RPC communication between devices and AI systems, with security authentication and a modular architecture.

MCP Server MAS Sequential Thinking is a server environment project focused on enhancing the sequential thinking process, providing modular design, scalability, and multi-language support, suitable for education, research, and application development.

mcpcap is a modular Python - based MCP server specifically designed for analyzing PCAP network packet capture files. It provides professional analysis tools for protocols such as DNS, DHCP, and ICMP, supports local file paths and remote URLs, does not require file upload, and provides network traffic analysis capabilities for LLMs through structured JSON responses.

This project designs and implements an architecture that connects the data space with generative AI. Through the Model Context Protocol (MCP) server as a secure middle layer, the language model can indirectly access the DuckDB database. It has the characteristics of modularity, extensibility, and log tracking, laying the foundation for future upgrades to the RAG architecture.

usaspending - mcp is a modular computing platform server designed to help AI agents access and interact with the USAspending.gov API, providing tools for retrieving and analyzing US government spending data.

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

This project is a TypeScript-based experimental platform for MCP servers, used for learning and testing integration with Claude Desktop and Cursor IDE. It extends the basic tutorial functions, providing a modular design and an extensible sandbox environment.

MCP Servers is a collection of servers and services for a Model Composition Platform (MCP), aiming to promote the integration and deployment of various AI/ML models and services. The project adopts a modular architecture, supporting standardized communication and scalable design, and includes various server types such as weather services.

This project is an MCP server based on the FastMCP framework, specifically designed to provide structured resume information of Frank Goortani. It supports accessing resume data through a standardized interface, including personal profiles, skills, work experiences, etc., and has a search function. The project uses a modular architecture, supports local and HTTP communication, and can be deployed to Cloudflare Workers.

This project builds a real - time AI agent architecture based on the MCP protocol. Through the decoupled design of the LangGraph agent and the remote MCP tool server, a modular and scalable multi - agent system is achieved. The project demonstrates how to integrate the LangGraph agent with a custom MCP server (supporting SSE and STDIO transmission) to achieve asynchronous non - blocking tool calls and support concurrent execution on multiple servers.

A Java - based MCP Server Factory project aiming to help understand and build other MCP servers, providing component understanding, templates, and best practices, adopting high - quality code standards and modular design.

A high - performance cancer genomics MCP server that enables seamless interaction with cBioPortal data through an asynchronous Python architecture. It adopts an enterprise - level modular design, boosting performance by 4.5 times.

An MCP server connecting AI assistants and the Spotify Web API, providing 29 tools such as music search, playback control, and playlist management, with a modular design and type - safe architecture.

MCP-CoConuT is a server based on the MCP protocol that provides continuous chain of thought (CoConuT) integration services for Cursor IDE. It supports thinking analysis, branch management, and quality assessment, adopts a modular design, and supports multi-language output.

This is an experimental project for MCP servers based on TypeScript, serving as a learning resource and testing platform, supporting integration with Calude Desktop and Cursor IDE. The project is derived from tutorials and has expanded more functions and tools, providing a modular design and an extensible sandbox environment.

MCP Base is a general model context protocol framework for building AI-driven applications. It provides standardized server and client implementations, supporting multiple integrations and modular design.

This project is an experimental platform for MCP servers based on TypeScript, used for learning and testing the integration with Calude Desktop and Cursor IDE. It extends tutorial examples, provides modular design and extensible functions, and is suitable for developers to explore MCP server development.

This project is an MCP server implementation based on Node.js, providing functions such as mathematical calculations, image processing, file system, and browser tools. It has a modular design and comprehensive test coverage.

This project demonstrates an intelligent agent based on LangChain, which integrates multiple service tools (search, weather, mathematical calculation) through the MCP protocol, adopts a modular design, and implements a perfect graceful shutdown mechanism.

This project showcases a lightweight multi-agent AI system that combines the Model Context Protocol (MCP) and Retrieval-Augmented Generation (RAG) for business analysis. The system provides statistical analysis of business data and knowledge retrieval functions for natural language queries by coordinating multiple dedicated tool servers. It features a modular design that facilitates expansion and the switching of LLM backends.

An AI model interaction server built on FastAPI and the MCP protocol, providing standardized context interaction, modular design, and asynchronous processing capabilities, simplifying model deployment and management.

The Model Context Protocol (MCP) Server is a modular server that supports various context - aware tasks. Currently, it includes research and web scraping functions, and is suitable for projects that require automated research or real - time data extraction.