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.

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.

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.

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.

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

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.

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.

The arXiv MCP Server is a service based on the Model Context Protocol (MCP) that allows users to interact with the arXiv API using natural language, enabling functions such as retrieving academic article metadata, downloading PDF files, searching the database, and loading articles into the context of a large - language model (LLM).

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

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

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.

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

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 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.

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 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.

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.

An interactive chat assistant that combines the capabilities of the Ollama large - model and PostgreSQL database access, supporting natural language querying of databases and generating SQL queries.

The ChatData MCP Server is a framework based on the Model Control Protocol, providing a toolset, prompt system, and resource management to enhance the capabilities of large language models.

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.

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.

The Didlogic MCP Server is a service that implements the Model Context Protocol (MCP), providing a standardized interface for large language models (LLMs) to interact with the Didlogic API, and supporting multiple functions such as balance management and SIP account management.

The APISIX MCP Server is a tool that bridges large language models and the APISIX Admin API, supporting the management of APISIX resources through natural - language interaction.

The Nextcloud MCP Server is a tool rewritten in TypeScript that allows large language models to interact with Nextcloud instances through the Model Context Protocol. It supports 30 operations such as notes, calendars, contacts, spreadsheets, and files, and especially provides a revolutionary unified file search function. It supports one - click cloud deployment on Smithery.

This project enables large language models to learn users' workflows by parsing MHT files generated by PSR.exe.

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 JIRA MCP Server is an intermediate service that enables large - language models to interact with JIRA, supporting JQL search and issue detail retrieval.

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.

Prompt Decorators is a framework for standardizing large - language - model prompt enhancement and transformation. It provides specification definitions and Python implementations, includes over 140 pre - set decorators, and supports MCP protocol integration.

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.

A tool that supports natural language querying and analysis of table data, supports multiple large language models, and can read table content from CSV files.

A memory server implementing the Model Context Protocol (MCP), providing persistent memory storage and retrieval functions based on a knowledge graph for large language models.

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