The Supabase MCP Server is a tool that connects Supabase projects with AI assistants. It standardizes the interaction between large language models (LLMs) and external services through the Model Context Protocol (MCP), enabling functions such as database management, configuration acquisition, and data querying.

The 302AI BrowserUse MCP Server is an AI-based browser automation server that enables natural language control of browsers and web research through the Model Context Protocol (MCP).

The Kubectl MCP Tool is a Kubernetes interaction tool based on the Model Context Protocol (MCP), allowing AI assistants to interact with Kubernetes clusters using natural language.

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.

MCP2Lambda is an MCP protocol server that runs AWS Lambda functions as tools for large language models (LLMs). AI models can call Lambda functions to access private resources and AWS services without code modification.

The YouTube MCP Server is a standardized interface implementation that allows AI language models to interact with YouTube content through protocols, providing functions such as video information retrieval, subtitle management, channel and playlist management.

DroidMind is a bridge tool for controlling Android devices via AI, implementing the Model Context Protocol (MCP), allowing AI to interact securely with Android devices through natural language.

The Notion MCP Server is a server implementation based on the Model Context Protocol (MCP) that allows AI assistants to interact with the Notion API through natural language, providing a complete set of tools and endpoints to read, create, and modify Notion content.

MCP2Lambda is an MCP server that allows AWS Lambda functions to be used as tools for large language models (LLMs) without modifying the code. It builds a bridge between AI models and Lambda functions through the Model Context Protocol (MCP), enabling models to access private resources and perform custom operations.

DaVinci Resolve MCP Server is a Model Context Protocol server that connects AI programming assistants (such as Cursor, Claude Desktop) with DaVinci Resolve, supporting natural language queries and control of DaVinci Resolve.

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.

Revit MCP integration is a bridge connecting Autodesk Revit and AI assistants, enabling model interaction through natural language.

The Kanboard MCP Server is a model context protocol server developed in Go that enables seamless integration between AI assistants and the Kanboard project management system. It supports managing projects, tasks, users, and workflows through natural language commands.

This project is a Model Context Protocol (MCP) adapter used to connect large language models (LLMs) with the Lisp development environment, supporting interaction through the lightweight Lisply protocol. The main functions include Lisp code evaluation, HTTP requests, and debugging support, suitable for scenarios such as AI-assisted symbolic programming and CAD design automation.

The Unity MCP Server is a C# - based Model Context Protocol (MCP) service used to connect the Unity editor with external large - language models (LLM) or cloud - based AI agents to achieve real - time automation and intelligent interaction.

MCPfinder is a local server tool that provides dynamic capability expansion for AI agents. By searching for and installing toolkits compatible with the MCP protocol, language models can obtain new functions on demand.

Model Context Protocol (MCP) .NET sample library, demonstrating how to use the MCP protocol to standardize the context interaction of large language models (LLMs) in .NET applications. It includes examples such as a YouTube subtitle extractor, supports flexible switching of LLM providers, and enables the construction of AI workflows.

ngspice-mcp is an MCP protocol-based server that provides a standardized interface for AI language models to access ngspice circuit simulation capabilities, supporting operations such as circuit loading, simulation execution, and data acquisition.

The YouTube MCP Server is a service that implements the Model Context Protocol (MCP). It provides a standardized interface for AI language models to interact with YouTube content, supporting functions such as video information retrieval, subtitle management, channel and playlist operations, etc.

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.

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.

Okta MCP Server is a server based on the Model Context Protocol that allows large - language models and AI agents to manage Okta organizations through natural language instructions, supporting management operations such as users, groups, applications, policies, and logs.

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.

PyMOL - MCP is a tool that integrates PyMOL with Claude AI through the Model Context Protocol (MCP), enabling control of molecular visualization and structural analysis through natural language.

GhidraMCP is a Ghidra plugin that enables AI - assisted binary analysis through the Model Context Protocol (MCP), connecting reverse engineering with AI assistants and providing functions such as natural language interaction, in - depth code analysis, and security vulnerability detection.

Auth0 MCP Server is an open - source project that integrates Auth0 management functions into LLMs and AI agents through the Model Context Protocol, allowing users to perform Auth0 management operations through natural language.

mcp2mqtt is a bridge project that connects IoT devices with large AI models, enabling natural language control of hardware devices through the MCP and MQTT protocols.

The Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers. It aims to provide large language models (LLMs) with secure and controllable access to tools and data sources. These servers demonstrate the diversity and scalability of MCP, covering various functions from file system operations to database integration, from web search to AI image generation.

The Maya MCP Server project implements the Model Context Protocol (MCP), allowing AI assistants to control Autodesk Maya through natural language. This project features a lightweight design, does not require installing plugins in Maya, communicates via Maya's default MEL script port, and supports dynamically adding new tool functions.

The Binalyze AIR MCP Server is a Node.js server implementing the Model Context Protocol (MCP), providing natural - language interaction capabilities for the Binalyze AIR digital forensics and incident response platform. It supports various functions such as asset management, evidence collection, endpoint operations, and policy management, authenticates through API tokens, and can be integrated with MCP clients such as Claude and Cursor.

The YouTube MCP Server is a tool for obtaining and extracting subtitles from YouTube videos, enabling AI language models to access and process video content.

This project is a document processing server based on the Model Context Protocol (MCP) standard. By building a vector database and an MCP interface, it enables AI assistants to access external document resources and break through the knowledge limitations of large language models. The project includes two major components: a document processing pipeline and an MCP server. It supports multiple embedding models and file formats and can be applied to scenarios such as querying the latest technical documents and understanding private code libraries.

This is an AWS Amplify Data MCP Server project that allows interaction with the data models of Amplify Gen2 applications through natural language, supports operations such as querying and modifying, and needs to be used with AI assistants like Claude.

An AI-driven MCP server for chart and prototype drawing, integrating multiple large language models and supporting the intelligent generation of draw.io format charts and HTML interactive product prototypes in multiple styles based on natural language descriptions.

Lucidity is a Model Context Protocol (MCP) server that aims to improve the quality of AI-generated code through intelligent prompt analysis. It provides structured guidance to help identify and resolve code quality issues, supports multiple programming languages, and can seamlessly integrate with AI assistants.

A code analysis server based on the MCP protocol that helps AI models understand and analyze codebases through natural language conversations, providing lightweight code exploration and understanding capabilities.

The YouTube data MCP server enables interaction between AI language models and YouTube content through a standardized interface

The Clockify MCP service is a server integrated with AI tools for managing time records in Clockify. Users can record time entries by sending prompts to large - language models.

An Excel file reading and writing service based on the Spring AI MCP framework, supporting integration with large language models for dynamic interaction

MCP2Serial is a bridge project connecting physical devices with large AI models, enabling intelligent control of the Internet of Things by controlling hardware devices through natural language.