# Data Access

This project implements a Model Context Protocol (MCP) server, which provides a standardized data source access method for LLMs and supports three core capabilities: resources, tools, and prompts.

The MCP Server is a Docker - based application that provides data access and tool operation functions via the MCP protocol and supports AI application integration.

An MCP server for Obsidian integration, providing functions for accessing vault contents, retrieving metadata, and API integration.

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. This project includes various types of server implementations, covering multiple domains such as file systems, databases, Git, and Slack, and supports TypeScript and Python SDKs.

This project is a collection of reference implementations of the Model Context Protocol (MCP), including MCP server implementations for various tools and services, aiming to provide secure and controllable access to tools and data sources for large language models (LLMs).

A server tool that helps users access and query databases through Legion Query Runner and the MCP protocol

Awesome MCP Servers is a curated list of Model Context Protocol (MCP) servers, covering multiple fields such as browser automation, art and culture, cloud platforms, command - line tools, communication, customer data platforms, databases, developer tools, file systems, finance and fintech, games, knowledge and memory, location services, marketing, monitoring, search, security, travel and transportation, version control, and other tools and integrations.

The Hugging Face MCP Server is a model context protocol service that provides read-only access to the Hugging Face Hub API, enabling LLMs like Claude to interact with Hugging Face's models, datasets, spaces, papers, and collections.