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.

Blender MCP VXAI is a powerful integration tool that allows users to control Blender through natural language to create and modify 3D models, animations, and scenes. It simplifies complex operations and supports real-time export to projects.

Jinni is an efficient tool for providing project context to large language models. It overcomes the limitations of reading files one by one by integrating relevant files and their metadata.

LLM Context is a tool that helps developers quickly inject code/text project content into the chat interface of large language models, supporting intelligent file selection and multiple integration methods.

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.

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.

The Alpaca MCP server is a model context protocol (MCP) service that implements the Alpaca trading API, allowing large language models to interact with the Alpaca trading system through natural language, supporting stock/options trading, portfolio management, and real-time market data acquisition.

The Rails MCP Server is a Model Context Protocol server implemented in Ruby, providing a standard interface for Rails projects to interact with large language models.

WireMCP is an MCP server that provides real-time network traffic analysis capabilities for large language models (LLMs). It realizes data capture, threat detection, and network diagnosis by integrating the Wireshark tool.

XiYan MCP Server is a model context protocol server based on XiYan-SQL that supports querying databases through natural language and provides options for integrating multiple LLM models and local deployment.

A knowledge graph memory server implemented in Swift, providing persistent memory functions for large - language models

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.

An MCP server that provides Notion integration, supporting operations such as page search, creation, update, and database management, enabling seamless interaction between language models and the Notion workspace.

The Azure Impact Reporting MCP Server is a tool that allows large language models to automatically parse user requests and submit reports on Azure resource issues. It supports multiple impact categories and automatically handles authentication and parameter extraction.

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.

HAProxy MCP Server is an HAProxy model context protocol server implemented in Go language. Through the HAProxy runtime API and the mcp-go library, it provides a standardized HAProxy management interface for large language models, supporting natural language interaction for load balancer management, monitoring, and traffic analysis.

The Strava MCP server is a middleware service that connects the Strava sports data API with language models, providing the ability to analyze, visualize sports data, and interact with social features.

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.

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.

DINO-X MCP is a project that enables large language models to perform fine-grained object detection and image understanding through DINO-X and Grounding DINO 1.6 API. It can achieve precise object positioning, counting, attribute analysis, and scene understanding, and supports natural language-driven visual tasks and workflow integration.

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 MSSQL MCP Server is an enhanced database management tool that provides comprehensive access to the Microsoft SQL Server database for language models through a standard interface. It supports 23 types of database operation tools, including advanced functions such as schema inspection, query execution, and stored procedure management.

The Wikipedia MCP Server is a tool that provides Wikipedia information query services for large language models. It enables real - time data access through a standardized protocol interface and includes functions such as searching, article retrieval, and summary generation.

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 MCP service for Ant Design components provides support for component documentation query and code generation for large language models

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.

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.

MCP Solver is a server that exposes SAT, SMT, and constraint - solving capabilities to large language models through the Model Context Protocol (MCP).

WebMCP is a project that allows websites to support client-side LLMs (Large Language Models). It enables the sharing of tools, resources, and prompts between websites and LLMs through a local WebSocket server without the need for API keys and supports multiple models.

The Heroku Platform MCP Server is a service designed for large language models, providing the ability to interact with Heroku platform resources.

A Python - based LINE MCP server that allows language models to read and analyze LINE conversation messages through a standardized interface. The project uses the FastAPI framework, supports text, sticker, and image message processing, and provides core functions such as message storage and API endpoints.

Rememberizer's MCP server provides the ability to interact with document and knowledge management APIs for large language models

The MCP GitHub Reader is a lightweight MCP server that integrates the content of GitHub repositories into the context of large language models, providing repository analysis, file access, intelligent filtering, and search functions.

HAL is an MCP server that provides HTTP API capabilities for large language models, supporting network requests through a secure interface and automatic generation of tools from OpenAPI specifications.

Deep-Co is a cross-platform chat client developed based on Compose Multiplatform. It supports multiple LLM API providers, including OpenRouter, Anthropic, Grok, OpenAI, etc., and is compatible with OpenAI API and local models. It has functions such as chat record management, prompt management, role adaptation, TTS, etc., and supports multiple languages and theme customization.

MacPilot CLI is an open-source tool that enables large language models to interact with the macOS system through the MCP protocol, providing system operation functions.

The Excalidraw MCP Server is an integration tool that provides a drawing API for large language models, supporting the creation, modification, and management of Excalidraw charts, including element control, resource management, and team collaboration functions.

This project is an MCP server for the Metasploit framework, providing a bridge between large - language models (such as Claude) and the Metasploit penetration testing platform, and supporting the control of complex security testing workflows through a natural language interface.