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.

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.

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.

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.

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.

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.

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.

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 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.

Binance MCP Server is a standardized interface service that provides Binance exchange data for large language models (LLMs), supporting functions such as real-time quotes, historical data, order book queries, and WebSocket push.

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.

File Context MCP is a TypeScript-based application that provides an API to query large language models (LLMs) through local file content. It supports multiple LLM providers (Ollama and Together.ai) and can process multiple file types to generate context-aware responses.

The Astra DB MCP server is a service that provides large language models (LLMs) with the ability to interact with the Astra database, extending the functions of LLMs as agents to interact with external systems.

This project is a collection of Model Context Protocol (MCP) servers specifically designed for DevOps tools and platforms. It enables large language models (LLMs) to directly interact with mainstream DevOps systems in a standardized way, achieving automated control of operations such as infrastructure, deployment pipelines, and monitoring.

SMCP Proxy is a reverse proxy designed for Model Context Protocol (MCP) services, providing a security layer with OIDC authentication, supporting enterprise - level authentication and authorization, and simplifying standardized interactions with large language models (LLMs).

Unity - MCP is a bridge tool that connects large language models (LLMs) and the Unity Editor. By exposing Unity Editor functions to AI clients, it enables an AI - driven automated development process. It supports custom tool extensions and currently provides core functions such as game object management, scene operations, and asset handling. It is mainly suitable for the Unity Editor environment.

The Firebolt MCP Server is a service that implements the model context protocol, which can connect LLMs (large language models) with the Firebolt data warehouse, enabling AI assistants to directly query data, generate insights, and access documentation resources.

This project implements a ClickHouse MCP server for seamless integration of the ClickHouse database with AI applications such as large language models (LLMs), supporting functions such as querying databases and obtaining table structures.

The GeoServer MCP Server is a server - side implementation of the Model Context Protocol (MCP) that connects large language models (LLMs) with the GeoServer REST API, enabling AI assistants to interact with geospatial data and services.

MCP Tools is a server project that implements the Model Context Protocol (MCP), providing file system and command execution tools for LLM clients such as Claude Desktop, and extending the local system interaction capabilities of large language models.

The SingleStore MCP Server is a service based on the Model Context Protocol (MCP) for managing context between large language models (LLMs) and external systems. It supports interacting with SingleStore through natural language and simplifies complex operations.

Stata-MCP is a tool that uses large language models (LLM) to assist users in completing Stata regression analysis. It supports multiple languages and platforms and provides a comprehensive guide from installation to advanced usage.

The Cloudflare MCP service is a standardized protocol based on the Model Context Protocol (MCP) for managing context interactions between large language models (LLMs) and external systems. This project provides an installer and an MCP server, supporting the management of various resources in a Cloudflare account, such as Workers, KV storage, R2 storage, and D1 databases, through natural language instructions. Users can perform various operations in a Cloudflare account using natural language via MCP clients such as Claude Desktop, VSCode (Cline), and Windsurf.

MCP-JaCoCo is a service tool that converts JaCoCo code coverage reports into a format suitable for large language models (LLMs), making AI-driven analysis more efficient

LLM Bridge MCP is a standardized interface service that supports unified calling and management of multiple large language models.

Deep Research MCP is a server project based on the Model Context Protocol (MCP), aiming to conduct comprehensive network research through Tavily's search and crawl APIs and integrate the data into structured Markdown documents to support high - quality content generation for large - language models (LLMs).

The ZBD MCP Server is a deprecated Bitcoin payment service used to add Bitcoin payment functionality to LLMs (Large Language Models). The project is developed based on the TypeScript SDK, supports handling Bitcoin Lightning Network payments through the ZBD API, and provides various payment tools and functions. Users need to migrate to the new MCP Server implementation.

This project enables large language models to directly understand and generate audio effect modules in the Max audio processing software through the Model Context Protocol (MCP). It supports explaining, modifying, and creating audio effect modules and provides an interaction interface with LLMs.

The Model Context Protocol (MCP) is an open - source protocol released by Anthropic, aiming to solve the standardization problem of connecting large language models (LLMs) with external data sources and systems. It provides a structured framework that enables models to integrate and utilize external context, thereby expanding their capabilities and improving response accuracy. MCP supports functions such as knowledge expansion, external tool calls, and pre - written prompts.

This is an MCP server framework based on Ruby, implementing the Model Context Protocol (MCP), allowing large language models to invoke tools (such as generating random numbers). The project includes functions such as protocol processing, tool management, and logging, and supports integration with LLMs such as Claude.

Auto Causal Inference is a project that uses large language models (LLMs) to automatically perform causal inference. Users only need to specify the treatment variable and the outcome variable, and the system can automatically complete the full - process analysis, including variable role identification, causal graph construction, effect estimation, and model validation. The project provides two agent architectures (LangGraph and MCP) to achieve this function, which is particularly suitable for causal problem analysis in the banking scenario.

finance-tools-mcp is an MCP server that provides financial analysis and insights for large language models (LLMs). It integrates multiple data sources and analysis tools, supporting multi - dimensional financial analysis such as stock data, market sentiment indices, and macroeconomic data.

CTX is a tool that connects code repositories with large language models (LLMs). By automatically generating structured context files, it solves the problem of low efficiency in code context transfer in AI development. It supports collecting information from various sources such as code files, Git repositories, and web pages, and can directly provide project context for AI assistants through the MCP server.

BinAssistMCP is an MCP service that connects Binary Ninja with large language models (LLMs), providing more than 40 reverse engineering tools and supporting dual transport protocols and intelligent context management.

Tome is a MacOS application (support for Windows and Linux is coming soon) developed by the Runebook team. It aims to simplify the use of local large language models (LLMs) with MCP servers. By integrating Ollama and managing MCP servers, users can quickly start chatting with MCP-powered models without dealing with complex configurations.

The Azure Impact Reporter MCP Server is a tool that enables large language models (LLMs) to automatically report resource issues to Azure. It processes user requests through natural language, automatically authenticates Azure accounts, and submits resource impact reports via the management API.

MetaTrader MCP Server is a Model Context Protocol server built on Python, aiming to achieve automated trading on the MetaTrader platform through AI large language models (LLMs). It supports integration with LLM tools such as Claude Desktop and Open WebUI and provides an HTTP server interface.