Building an MCP Server for SQLite Database Integration

Overview

This tutorial demonstrates how to create an MCP (Model-Centric Protocol) server that interacts with a local SQLite database. The server provides functionalities to query and explore data stored in a SQLite database.

Database Structure

The example uses a simple SQLite database with a table called demo containing two fields:

• idno - ID number
• Name

The table contains several records with ID numbers and corresponding names.

Server Features

The MCP server provides two main functionalities:

1. Resource listing: View the database schema, including all table structures
2. Query tool: Execute SQL queries directly against the database

Examples of operations:

• Viewing table schema by using list resource
• Running SQL queries like SELECT * FROM demo
• Applying conditions such as SELECT * FROM demo WHERE idno=3

Implementation

The code implementation requires:

1. Importing necessary modules:
   • sqlite3 for database connectivity
   • fast_mcp for simplified MCP server creation
2. Creating an MCP server instance:
   mcp = FAST_MCP("SQLite Explorer")
3. Defining resources with decorators:
   @mcp.resource("schema://main") def get_schema(): # Connect to database # Execute SQL to get schema information # Return formatted results
4. Defining tools with decorators:
   @mcp.tool def query_data(sql): # Connect to database # Execute the provided SQL query # Return results or error messages

Error Handling

The server includes basic error handling to provide appropriate error messages when queries fail (e.g., "no such table demo1" when a non-existent table is queried).

Conclusion

By using the FAST_MCP framework, this implementation allows large language models to interact with local SQLite databases, enabling deeper integration between AI systems and local data sources.