mcp-server.sqlite MCP Server

Use This MCP server To

Execute dynamic SQL SELECT queries via AI model requests List and inspect SQLite database tables and schemas Synthesize business insights from SQLite data using AI Integrate SQLite data querying into AI-powered applications Enable AI models to interactively manage SQLite databases Automate data retrieval and analysis from SQLite for reports Support multi-step reasoning with live database context Facilitate AI-driven data exploration in SQLite environments

README

SQLite MCP Server

A Model Context Protocol (MCP) server implementation using TypeScript for interacting with an SQLite database. This server provides an interactive interface for executing SQL queries, managing database schemas, and synthesizing business insights—all within an extensible protocol framework.

Not familiar with MCP? Check out the What is an MCP? section below.

Features

Command	Description	Example
`list_tables`	List all tables on the SQLite database	-
`read_query`	Execute SELECT queries on the SQLite database	`SELECT * FROM users WHERE age > 18`

Installation & Setup

git clone https://github.com/javsanmar5/mcp-server.sqlite.git
cd mcp-server.sqlite

Since this hasn't been published as an npm package yet, we'll focus on the Docker installation method:

1. Build the Docker image

docker build -t mcp/sqlite .

2. Configure your AI client

Add the following to your AI client's configuration file:

"mcpServers": {
  "sqlite": {
    "command": "docker",
    "args": [
      "run",
      "--rm",
      "-i",
      "-v",
      "mcp-test:/mcp",
      "mcp/sqlite",
      "--db-path",
      "test_db.sqlite3"
    ]
  }
}

If you don't know what is that json file you might want to see the Client Configuration Guide.

3. Restart your AI client

After restarting, the MCP Tools should be available in your AI client's interface. On Windows, you may need to manually kill the process for the changes to take effect.

Documentation

What's an MCP?

Model Context Protocol (MCP) is a standardized way for AI models to interact with external tools and services. It allows AI assistants to perform actions like running database queries, accessing external APIs, or manipulating files through a defined protocol interface.

MCPs extend AI capabilities beyond conversation by providing structured access to tools and data sources without requiring direct integration into the AI model itself.

Tutorial: Setting up with Claude Desktop

Claude Desktop is one of many AI clients that support MCP servers. Here's how to set it up on Windows:

Press Windows Key + R to open the Run dialog
Type %appdata%\Claude and press Enter
Create a new file called claude_desktop_config.json if it doesn't exist already
Add the configuration from step 2 of the setup instructions above
Save the file and restart Claude Desktop
You should now see the SQLite tools available in your Claude interface

License

This project is licensed under the MIT License.

Contributing

This project was created primarily for learning purposes. However, if you'd like to contribute, feel free to submit a Pull Request and I'll review it.

Thanks for your interest!

mcp-server.sqlite FAQ

How do I install mcp-server.sqlite using Docker?

Clone the repo, build the Docker image with 'docker build -t mcp/sqlite .', then run the container.

Can mcp-server.sqlite execute all types of SQL queries?

It primarily supports SELECT queries and schema inspection commands like listing tables.

How does mcp-server.sqlite integrate with AI models?

It exposes SQLite data and query capabilities via MCP, allowing models to request data and execute queries in real time.

Is mcp-server.sqlite limited to SQLite databases only?

Yes, this server is specifically designed for SQLite, leveraging its lightweight and file-based architecture.

What programming language is mcp-server.sqlite implemented in?

It is implemented in TypeScript for robust type safety and extensibility.

Can I extend mcp-server.sqlite to support other SQL commands?

Yes, the server is built on an extensible protocol framework allowing additional commands to be added.

How does mcp-server.sqlite ensure secure query execution?

It scopes query execution within the MCP framework, enabling controlled and observable interactions.

Which AI model providers are compatible with mcp-server.sqlite?

It works with any MCP-compatible AI models, including OpenAI, Anthropic Claude, and Google Gemini.