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.

An MCP server that integrates AI models with WinDbg/CDB for analyzing Windows crash dump files and remote debugging, supporting natural language interaction to execute debugging commands.

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.

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.

The AI Infrastructure Agent is an intelligent system that allows users to manage AWS cloud resources through natural language commands. It uses AI models to convert user requirements into executable AWS operations and provides web dashboards, state management, and security protection functions.

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.

BloodHound - MCP is a project that integrates the Model Context Protocol (MCP) server with BloodHound, analyzing Active Directory security data through natural language.

AWS MCP is a service based on the Model Context Protocol that allows querying and managing AWS resources through natural language, similar to an alternative to Amazon Q.

BloodHound - MCP is a tool that integrates the Model Context Protocol (MCP) server with BloodHound. It analyzes Active Directory attack paths through natural language and provides more than 75 dedicated tools for AD security assessment.

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.

XiYan MCP Server is a Model Context Protocol server based on XiYan - SQL, which supports querying databases through natural language, provides multiple LLM model configurations and database connection methods, and is suitable for local or remote deployment.

Lokka is a server based on the Model - Context - Protocol (MCP) for querying and managing Azure and Microsoft 365 tenants by operating Microsoft Graph and Azure RM APIs through natural language.

The Elasticsearch MCP Server project enables natural - language interactive queries of Elasticsearch data through the Model Context Protocol (MCP).

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.

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.

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 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.

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.

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.

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.

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

The Meta Prompt MCP project simulates a multi - agent collaboration system through a single language model, realizing task decomposition and expert consultation functions, and simplifying the process of solving complex problems.

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.

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.

An MCP server implementation for the Deepseek R1 language model based on Node.js, supporting an 8192-token context window, providing stable Claude Desktop integration and model parameter configuration.

The official MCP server of phospho, implementing the model context protocol, supporting the control of physical robots through natural language, and providing functions for performing actions and camera image streaming.

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

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.

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.

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 Railway MCP Server is a service based on the Model Context Protocol (MCP) for managing the infrastructure of Railway.app through natural language, including deploying services, managing variables, and monitoring deployments.

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.

Beanquery MCP is an experimental implementation of the Model Context Protocol (MCP) server for interacting with Beancount ledger files, enabling querying and analysis of financial data through the BQL query language and the beanquery tool.

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.