Build Your First MCP Server in Python: From Zero to Claude Integration

#mcp #claudecode #python #ai

Building an MCP server gives Claude direct access to your services, databases, and APIs. Here's how to build one from scratch in Python.

What You're Building

An MCP server that Claude can use to query a SQLite database with natural language.

Setup

mkdir my-mcp-server && cd my-mcp-server
python3 -m venv .venv && source .venv/bin/activate
pip install mcp

The Minimal MCP Server

#!/usr/bin/env python3
import sqlite3
import json
from mcp.server import Server
from mcp.server.stdio import stdio_server
from mcp.types import Tool, TextContent

server = Server('sqlite-explorer')
db = sqlite3.connect('data.db', check_same_thread=False)
db.row_factory = sqlite3.Row

@server.list_tools()
async def list_tools() -> list[Tool]:
    return [
        Tool(
            name='query_database',
            description='Execute a read-only SQL query and return results as JSON.',
            inputSchema={
                'type': 'object',
                'properties': {
                    'sql': {'type': 'string', 'description': 'SELECT query to execute'}
                },
                'required': ['sql'],
            },
        ),
        Tool(
            name='list_tables',
            description='List all tables in the database with their schemas.',
            inputSchema={'type': 'object', 'properties': {}},
        ),
    ]

@server.call_tool()
async def call_tool(name: str, arguments: dict) -> list[TextContent]:
    if name == 'list_tables':
        tables = db.execute(
            "SELECT name FROM sqlite_master WHERE type='table' ORDER BY name"
        ).fetchall()
        result = {}
        for table in tables:
            schema = db.execute(f"PRAGMA table_info({table['name']})").fetchall()
            result[table['name']] = [{'name': c['name'], 'type': c['type']} for c in schema]
        return [TextContent(type='text', text=json.dumps(result, indent=2))]

    elif name == 'query_database':
        sql = arguments.get('sql', '')
        if not sql.strip().upper().startswith(('SELECT', 'WITH')):
            return [TextContent(type='text', text='Error: Only SELECT queries allowed.')]
        try:
            rows = db.execute(sql).fetchall()
            return [TextContent(type='text', text=json.dumps([dict(r) for r in rows], indent=2, default=str))]
        except sqlite3.Error as e:
            return [TextContent(type='text', text=f'Query error: {str(e)}')]

async def main():
    async with stdio_server() as (read_stream, write_stream):
        await server.run(read_stream, write_stream, server.create_initialization_options())

if __name__ == '__main__':
    import asyncio
    asyncio.run(main())

Seed Some Test Data

import sqlite3
db = sqlite3.connect('data.db')
db.executescript("""
    CREATE TABLE IF NOT EXISTS users (
        id INTEGER PRIMARY KEY, name TEXT, email TEXT UNIQUE,
        created_at TEXT DEFAULT (datetime('now')), plan TEXT DEFAULT 'free'
    );
    INSERT OR IGNORE INTO users (name, email, plan) VALUES
        ('Alice', 'alice@example.com', 'pro'),
        ('Bob', 'bob@example.com', 'free');
""")
db.commit()

Connect to Claude Code

Add to ~/.claude/claude_desktop_config.json:

{
  "mcpServers": {
    "sqlite-explorer": {
      "command": "/path/to/.venv/bin/python",
      "args": ["/path/to/server.py"],
      "cwd": "/path/to/my-mcp-server"
    }
  }
}

Restart Claude Code. Now ask:

"How many users are on the pro plan?"
"What is the total revenue from orders this week?"
"Show me users who have placed more than one order"

Claude fetches real data and reasons about it.

Key Security Rules Before Publishing

[ ] Validate all input parameters
[ ] Read-only by default -- explicit opt-in for writes
[ ] No shell=True subprocess calls
[ ] Error messages don't expose file paths or internals
[ ] No hardcoded credentials -- env vars only
[ ] Tool descriptions are concise (no embedded instructions)

For automated security scanning covering 22 vulnerability patterns:

MCP Security Scanner Pro ($29) ->

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