MCP Database Server
by manpreet2000
The MCP Database Server allows Large Language Models (LLMs) to interact with databases through natural language. It currently supports MongoDB and plans to support PostgreSQL, CockroachDB, and Redis.
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What is MCP Database Server?
The MCP Database Server is a Model Context Protocol (MCP) server implementation that enables Large Language Models (LLMs) to perform database operations using natural language queries. It acts as a bridge between LLMs and databases, translating natural language requests into database commands.
How to use MCP Database Server?
To use the server, you need to clone the repository, install dependencies, build the TypeScript code, and configure your database connection in the Claude Desktop configuration file. Then, you can use natural language commands with your LLM to interact with the database.
Key features of MCP Database Server
Database operations through natural language
Supports MongoDB (currently)
Future support for PostgreSQL, CockroachDB, and Redis
Provides tools for listing collections, querying documents, inserting, deleting, and aggregating data
Use cases of MCP Database Server
Enabling LLMs to retrieve information from databases
Allowing LLMs to modify data in databases
Building conversational interfaces for database management
Automating database tasks with natural language commands
FAQ from MCP Database Server
What databases are currently supported?
What databases are currently supported?
Currently, only MongoDB is supported. Support for PostgreSQL, CockroachDB, and Redis is planned for the future.
What Node.js version is required?
What Node.js version is required?
Node.js v20.12.2 or higher is required.
How do I configure the database connection?
How do I configure the database connection?
You need to configure your database connection in the Claude Desktop configuration file (claude_desktop_config.json).
What kind of operations can I perform on MongoDB?
What kind of operations can I perform on MongoDB?
You can list collections, query documents with filtering and projection, insert documents, delete documents, and perform aggregate pipeline operations.
How can I contribute to the project?
How can I contribute to the project?
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.