sqlite-mcp-server

sqlite-mcp-server

0
databases

The SQLite MCP Server is designed to perform SQLite database operations using the Model Context Protocol, offering features such as SQL queries, table management, and business insights tracking. It supports easy deployment through Docker and Nixpacks and provides remote server connectivity.

SQLite MCP Server

A Model Context Protocol (MCP) server that provides SQLite database operations through a standardized interface.

Features

  • In-memory SQLite database (configurable for file-based storage)
  • SQL operations (SELECT, INSERT, UPDATE, DELETE)
  • Table management (CREATE, LIST, DESCRIBE)
  • Business insights memo tracking
  • Docker support for easy deployment

Development & Deployment

Local Development

# Install dependencies and build
npm install
npm start

Docker Deployment

# Build and run with Docker
docker build -t sqlite-mcp-server .
docker run -d --name sqlite-mcp sqlite-mcp-server

Nixpacks Deployment

The application can be easily deployed using Nixpacks with platforms like Railway, Coolify, or Render:

# Deploy with Nixpacks
nixpacks build . --name sqlite-mcp-server

No additional configuration is needed as the project includes a Dockerfile.

Available Tools

  1. read_query: Execute SELECT queries
  2. write_query: Execute INSERT, UPDATE, or DELETE queries
  3. create_table: Create new tables
  4. list_tables: List all tables in the database
  5. describe_table: View schema information for a table
  6. append_insight: Add business insights to the memo

Remote Server Connection

To connect using SSE in n8n:

  1. Add an MCP Client node
  2. Configure SSE connection:
    • SSE URL: http://localhost:3000/sse
    • Messages Post Endpoint: http://localhost:3000/messages
    • No additional headers required

Example Usage

// Create a table
await callTool('create_table', {
  query: 'CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT)'
});

// Insert data
await callTool('write_query', {
  query: 'INSERT INTO users (name) VALUES ("John Doe")'
});

// Query data
const result = await callTool('read_query', {
  query: 'SELECT * FROM users'
});

Environment Variables

None required by default. If using file-based storage, modify the database path in src/index.ts.

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

ISC