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.

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).

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.

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.

This project is a document processing server based on the Model Context Protocol (MCP) standard. By building a vector database and an MCP interface, it enables AI assistants to access external document resources and break through the knowledge limitations of large language models. The project includes two major components: a document processing pipeline and an MCP server. It supports multiple embedding models and file formats and can be applied to scenarios such as querying the latest technical documents and understanding private code libraries.

MCP-DBLP is a service based on the Model Context Protocol (MCP) that provides large language models with the ability to access the DBLP computer science literature database, including functions such as search, citation processing, and BibTeX export.

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.

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.

BioMCP is a biomedical R & D server based on the MCP protocol. By integrating protein databases and analysis tools, it enhances the capabilities of large language models in the field of protein structure analysis.

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.

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.

This project implements a server based on the MCP protocol for querying the French legal database via the Legifrance API, supporting integration with large language models such as Claude and providing search functions for legal provisions, codes, and precedents.

A natural language MySQL database query system based on MCP and the QWEN large model, providing GUI interface support

YDB MCP is a tool that provides Model Context Protocol services for the YDB database, supporting interaction with large language models through the MCP protocol to enable natural language database operations.

The Unified MCP Tool Graph is a research - driven project that provides an intelligent infrastructure layer for large language models (LLMs) and agent AI systems to dynamically retrieve the most relevant tools by aggregating and structuring tool APIs from different MCP servers into a centralized Neo4j graph database.

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. The project includes implementations of various functional servers, covering areas such as file systems, databases, search, and API integration, and supports development with TypeScript and Python SDKs.

Kolada MCP Server is an intelligent middleware that connects large language models with the Swedish Kolada statistical database, providing functions such as semantic search, KPI analysis, and multi - year comparison, simplifying the query and interpretation of public - sector data.

A lightweight MCP server that allows large language models to interact with SQLite databases autonomously

The Firestore Advanced MCP server enables large language models like Claude to fully interact with the Firebase Firestore database, supporting operations such as CRUD, advanced queries, and transaction processing.

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 an implementation of an MCP server based on ODBC, providing large language models with the ability to transparently access ODBC data sources through TypeScript and node - odbc. It supports multiple database management systems, including Virtuoso, and provides a rich set of tools for data query and management.

This project provides a series of Model Context Protocol (MCP) server implementations based on the Quarkus framework, used to extend the capabilities of large language model (LLM) applications that support MCP. It includes various services such as JDBC databases, file systems, JavaFX drawing, Kubernetes, and containers.

This project installs an MCP (Model Context Protocol) server to provide the configured Oracle database tables/columns as context to the LLM (Large Language Model), enabling the LLM to interact with the Oracle database, generate SQL statements, and return results through LLM prompts.

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers, enabling large language models (LLMs) to securely and controllably access tools and data sources. The project includes server implementations with various functions, such as file system operations, database access, Git management, Slack integration, etc., and supports TypeScript and Python SDKs.

XiYan MCP Server is a model context protocol server based on XiYan - SQL. It supports querying databases through natural language and provides multiple model configuration options, including general large models, SOTA text - to - SQL models, and local models. It is suitable for scenarios with different security and performance requirements.

This project showcases multiple Model Context Protocol (MCP) servers integrated with Microsoft Azure, which enable large language models (LLMs) to securely access Azure tools and data sources, including AI agent services and various database services.

The SQL Server MCP Server is a tool based on the Model Context Protocol that allows large language models to query and inspect SQL Server databases through a standardized protocol, providing database query and schema inspection functions.

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers for providing large language models (LLMs) with secure and controlled access to tools and data sources. The project includes various functional servers, such as file system operations, Git integration, database access, etc., and supports rapid development of new services through TypeScript and Python SDKs.

A RAG system built with open-source embedding models, vector databases, and the Gemini large language model, supporting local document processing and dynamic index update.

Cloudflare MCP Server is a standardized protocol service based on the Model Context Protocol (MCP) for managing context interactions between large - language models (LLMs) and external systems. Through this service, users can use natural language instructions to operate various resources in their Cloudflare accounts, such as Workers, KV storage, R2 storage, and D1 databases.

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

The Neon MCP Server is a server based on the Model Context Protocol (MCP) standard, used to manage the context interaction between large - language models (LLMs) and the Neon database. It supports performing database operations through natural language instructions, such as creating projects, managing branches, running SQL queries, and migrations.

The IDA MCP Server is a model context protocol server for IDA interaction and automation, providing tools for reading the IDA database through large language models.