The AWS MCP Servers are a set of dedicated servers based on the Model Context Protocol, offering various AWS-related functions, including document retrieval, knowledge base query, CDK best practices, cost analysis, image generation, etc., aiming to enhance the integration of AI applications with AWS services through a standardized protocol.

Sail is a project aiming to unify stream processing, batch processing, and compute - intensive (AI) workloads. It provides an alternative to Spark SQL and Spark DataFrame APIs and supports both standalone and distributed environments.

Eino is an LLM application development framework designed specifically for Golang, aiming to simplify the AI application development process through concise, scalable, reliable, and efficient component abstraction and orchestration capabilities. It provides a rich component library, powerful graphical orchestration functions, complete stream processing support, and a highly scalable aspect mechanism, covering the full-cycle toolchain from development to deployment.

Coco AI is a unified search platform that integrates enterprise applications and data (such as Google Workspace, Dropbox, GitHub, etc.), providing cross-platform search and AI-driven team chat functions, aiming to improve work efficiency and collaboration experience.

MCPAdapt is an open - source project aiming to seamlessly integrate the tools of over 650 MCP servers into various agent frameworks, enabling developers to easily use these tools in their agent workflows.

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.

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.

MCPEngine is a production-grade implementation of the Model Context Protocol (MCP), providing standardized interfaces for large language models (LLMs). It supports functions such as OAuth authentication, resource management, and tool invocation, aiming to become the 'REST of the LLM world' framework.

adb - mcp is a proof - of - concept project aiming to provide an interface for LLMs through the MCP protocol to create an AI agent for controlling Adobe tools (such as Photoshop and Premiere). This project includes the MCP server, Node command proxy server, and Adobe application plugins, supporting natural language instruction operations on Adobe software and suitable for image and video editing automation.

Awesome MCP Security is a collection of resources related to the security of the Model Context Protocol (MCP), including security considerations, papers, videos, articles, tools, and servers, aiming to help users understand and address MCP - related security challenges.

Open Data MCP is an open - source project aiming to quickly connect public data sets to LLM applications through the MCP protocol, enabling convenient access to open data and community - based publishing.

Open Data MCP is an open - source project aiming to quickly connect public data sets to LLM applications through the MCP protocol. The project provides a CLI tool to achieve a 2 - minute connection (currently supporting Claude) and establishes a community collaboration framework that allows developers to easily contribute and publish public data sets. The core goal is to build an infrastructure that connects all LLM applications with millions of public data sets.

This project is a collection of MCP servers designed for Kali Linux, aiming to enhance reverse engineering, security testing, and automation workflows. It integrates tools such as Nmap and Wireshark and provides Docker sandbox support.

awesome - mcp is a project that collects Model Context Protocol (MCP) servers/clients, aiming to simplify the integration of large language models with external systems through a standardized protocol.

The MCP Context Template is a repository for centrally managing AI tool contexts, aiming to reduce the cost of context sharing and improve development efficiency, providing a unified AI collaboration standard and document structure for teams.

This project is a Python - based implementation of the MCP (Model Context Protocol) server and client, aiming to provide standardized interfaces for AI models, unify the tool call formats of different large - model vendors, and integrate document search functions for multiple AI frameworks.

Memgraph MCP Server is a lightweight implementation of the Model Context Protocol (MCP) server, aiming to connect the Memgraph graph database with large language models (LLMs) and provide Cypher query execution and schema information acquisition functions.

The React Native MCP server is a platform that provides comprehensive development tools, aiming to optimize the React Native development experience. It includes functions such as project initialization, version management, automated upgrades, and Expo integration. It simplifies the development process through AI assistance.

Zetmem is an AI-assisted memory server project based on the Zettlekasten method, aiming to provide a persistent context memory system for AI programming tools such as Claude, supporting code memory storage, retrieval, and intelligent evolution across sessions and projects.

The Pega DX MCP Server is an experimental project aiming to transform Pega Infinity™ applications into an intuitive conversational experience through the Model Context Protocol (MCP). It serves as a bridge between the Pega DX API and the natural language interface, enabling GenAI agents, IDEs, and other MCP-supported tools to interact with Pega Infinity™ applications using simple human-readable commands.

FridaC2MCP is a proof - of - concept project that exposes the capabilities of the Frida dynamic instrumentation tool as a remote MCP server through HTTP streaming, aiming to achieve remote and automated mobile application security testing. The project is designed to run on a rooted Android device, allowing clients to analyze and manipulate running applications over the network.

The Neural Child Development System is a breakthrough artificial intelligence framework that reconstructs the learning method of neural networks by simulating human psychological development stages (including cognitive, emotional, and social growth). This system integrates developmental psychology theories (such as Piaget's cognitive development stages and attachment theory) and neuroscience principles to build a complex architecture including perceptual processing, emotional regulation, memory systems, and psychological components, aiming to create AI with real emotional intelligence and natural development capabilities.

This project is a research and documentation on the Model Context Protocol (MCP), including technical analysis, implementation solutions, usage guides, and other resources, aiming to comprehensively introduce the MCP ecosystem.

An MCP server built on Deno and TypeScript, providing context information related to Terragrunt documentation and GitHub issues, aiming to improve IDE support and AI assistance accuracy when writing IaC configurations.

The Chroma MCP Server is a model context protocol server designed for the Chroma vector database, aiming to provide persistent working memory functions for AI-assisted development, supporting cross-session context storage and semantic retrieval.

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.

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.

CrewAI Crew is a multi - agent AI system project based on the crewAI framework, aiming to complete complex tasks through configuration and collaboration.

ResearchMCP is a research tool that combines the Model Context Protocol (MCP) with multiple search engines, aiming to provide research capabilities similar to ChatGPT DeepResearch.

This project provides a Python template for quickly building a Model Context Protocol (MCP) server, aiming to simplify and optimize the AI-assisted development process.

This project provides a comprehensive guide for implementing a Model Context Protocol (MCP) server for Cursor AI, including basic concepts, implementation steps, code examples, and integration requirements, aiming to enhance the AI's capabilities through custom tools.

MCP-KG-Memory is an MCP server with a long-term memory layer based on a knowledge graph, aiming to solve the context forgetting problem of AI programming assistants. It persistently stores project goals, constraints, strategies, and user preferences through Neo4j, enabling semantic retrieval and active learning, and endowing the AI assistant with continuous memory and context awareness capabilities.

KiMCP is a server project based on the Model Context Protocol (MCP), aiming to integrate local Korean APIs (such as Naver, Kakao, TMAP, etc.) into LLM applications, providing various service functions including blog search, news retrieval, and map navigation.

VkRunner is a Vulkan shader testing tool based on Piglit's shader_runner, aiming to support test scripts as similar as possible to Piglit's shader_test format. It supports writing shaders in GLSL or SPIR-V and provides a rich set of test commands to verify shader behavior, including drawing, computing, and probe detection functions.

Awesome MCP Servers is a curated list of Model Context Protocol (MCP) servers, covering multiple categories such as file systems, databases, web search, version control, communication, and developer tools, aiming to expand the capabilities of AI models.

EasyChatDM is an educational project for creating simple MCP server tools, aiming to provide random decision - making tools for D&D games through generative AI.

The MCP Partner Hub is a resource library that centrally displays and compares MCP (Model Context Protocol) servers provided by different ISV partners, aiming to help users discover, evaluate, and select MCP servers that meet their needs.

This is a server project based on Model Context Protocol (MCP), aiming to integrate with Kakao Mobility and Kakao Map APIs to provide route planning and location search services suitable for the South Korean environment.

The UI5 MCP Server is a tool based on the Model Context Protocol, designed for UI5 application development. It provides functions such as project creation, code analysis, API documentation query, and development guidance, aiming to enhance the experience of developers when using AI - assisted tools.