The AI Development Assistant MCP Server is an AI - based code development toolkit that provides functions such as code architecture generation, UI screenshot analysis, and code review, specifically designed for Cursor.

napi is a tool developed by NanoAPI, aiming to automatically analyze software architecture complexity, support extracting functional modules from the codebase, provide both CLI and UI operation methods, and be compatible with mainstream CI/CD platforms to help developers optimize architecture design.

ATLAS is an intelligent task and knowledge management system built on TypeScript and Neo4j, designed for LLM agents, providing a three - layer management architecture for projects, tasks, and knowledge.

The Figma MCP Server project integrates with the Figma API through clients such as Claude, supports file reading and design system management functions, has an extensible architecture but is currently read - only due to API limitations.

DB MCP Server is a multi-database supported server that implements the Model Context Protocol (MCP) and provides AI assistants with the ability to access databases in a structured manner. It supports MySQL and PostgreSQL, can connect to multiple databases simultaneously, automatically generates dedicated tools, and follows a clear architecture design.

rag - mcp is an over - designed retrieval - augmented generation system that provides multiple text search modes (semantic search, question - answer search, style search) through a Python server. It uses PostgreSQL and pgvector to store text embedding vectors, supports interaction with AI agents, and has a complex but scalable architecture.

MCP Architect is a service that provides comprehensive architecture expertise, supporting multiple architecture fields through professional agents, resources, and tools.

An MCP server implementation designed for the Claude desktop application, providing persistent memory functions for large language models, including a tiered memory architecture, multiple memory types, and semantic search features.

The Semantic D1 MCP server is an introspection tool for Cloudflare D1 databases based on the semantic intent pattern. It is designed with a hexagonal architecture and provides functions such as database schema analysis, relationship extraction, schema validation, and optimization suggestions.

The RevitMCP project introduces natural language interaction capabilities to Revit, realizes BIM modeling automation through the MCP protocol, adopts a hierarchical architecture design, supports multi - turn dialogue and parameter completion, and significantly improves modeling efficiency.

MCP Server Semgrep is a server that complies with the Model Context Protocol standard, integrating the Semgrep static analysis tool with an AI assistant to provide code security analysis, quality improvement, and vulnerability detection functions. The project simplifies the architecture design, supports multi - platform operation, can be installed in multiple ways, and provides a rich set of code analysis functions.

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

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.

The GLM-4.6 MCP Server is an enterprise-level architecture consulting protocol bridging service that connects Claude 4.5 Sonnet and GLM-4.6 through the model context protocol, providing system design, scalability patterns, and technical decision-making support. It supports functions such as code architecture analysis, system architecture design, and decision review.

An MCP server implementation designed for the Claude desktop application, providing persistent memory functions, including a tiered memory architecture, multiple memory types, and semantic search features.

The Gemini UI Design Server is an enterprise-level UI/UX design and front-end implementation expert system based on the MCP protocol, providing professional UI component design, code review, front-end code generation, and architecture consultation services by integrating Google Gemini 2.5 PRO.

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.

This project is part of the Model Context Protocol (MCP) ecosystem. It provides an MCP server that interacts with the Status Invest API for querying stock market data, such as stock prices, indicators, and payment dates. The project adopts a layered architecture design, including the domain layer, infrastructure layer, application layer, and interface layer, and supports data validation and external API integration.

The MCP server based on the GLM-4.5V model provides intelligent image analysis functions, supporting image acquisition from file paths or the clipboard. It is specifically designed for code content extraction, architecture analysis, error detection, and documentation generation.

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

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.

This project is a command - line interface (CLI) tool that integrates Arcee AI, TESS, and MCP services. It adopts the Clean Architecture and DDD design principles to provide an abstract layer for unified access to multiple artificial intelligence services.

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.

The AWS Boto3 MCP Server is a Python-based MCP service designed to monitor and manage AWS account resources by executing code through the Boto3 client of the AWS Python SDK. The service uses a front - end MCP server and a back - end AWS LightSail container architecture and ensures security by requiring the client to provide valid AWS credentials.

This is a FastAPI service template based on Python, designed with Clean Architecture and SOLID principles, providing features such as API documentation, asynchronous tasks, WebSocket, database repository pattern, identity authentication, etc., and supporting multi - stage Docker builds to optimize image size.

MCP Server Tools is an innovative API project based on the Model Context Protocol (MCP). It combines traditional API endpoints with intelligent model communication, adopts a domain - driven design (DDD) architecture, and provides a secure and extensible API experience.

A user management system designed based on FastAPI and Clean Architecture, using CSV files to store data, implementing user CRUD, batch import, and age statistics functions.

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.

An implementation of the MCP architecture server based on FastAPI, using the Model-Controller-Provider design pattern, providing high-performance REST API services, including functions such as automatic documentation generation and data validation.

This project is an MCP server for operating TinySA devices via serial port. It provides a Python - based tool interface, supports functions such as command execution, version acquisition, and image capture, and is designed with a Tkinter GUI and multi - thread architecture.

An AI software architect server based on the MCP protocol that can analyze codebases to generate product requirement documents (PRDs) and provide reasoning assistance for complex coding tasks. It uses a multi-model architecture and intelligent agent design.

This project is a tutorial for building a Model Context Protocol (MCP) server based on Google's Gemini 2.0 model. It includes a complete code implementation, demonstrating how to enable AI models to seamlessly access external tools (such as the Brave Search API) through the MCP standard, and provides an example of a flexible architecture design.

MCP Servers is a collection of services based on the Model Context Protocol, providing intelligent function support for the Cursor IDE. It includes a sample service and a weather service and adopts a three - layer architecture design.