mcp-sql-query

mcp-sql-query

An MCP server providing SQLite database access for AI agents, enabling SQL execution, schema inspection, CRUD operations, and data export.

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MCP SQL Query — SQLite Database Operations for AI Agents

An MCP server that gives AI agents SQLite database access: execute SQL, inspect schemas, CRUD operations, export to JSON/CSV — 13 tools, zero dependencies, pure Python stdlib.

Features

  • 13 MCP Tools: execute_sql, execute_batch, list_tables, table_schema, create_table, insert_row, insert_batch, select_rows, update_rows, delete_rows, export_json, export_csv, database_info
  • Zero dependencies — pure Python stdlib (sqlite3, json, re, os)
  • SQL injection prevention — table name validation with regex
  • Batch transactions — execute multiple statements atomically with rollback
  • Data export — JSON array or CSV string output
  • In-memory or file-based — use :memory: for ephemeral DBs or file paths for persistence
  • STDIO JSON-RPC mode — drop-in for Claude Desktop, Hermes, or any MCP client

Quick Start

python -m src.server --stdio    # STDIO mode
python -m src.server --manifest # Print manifest

Use as a library

from src.server import MCPSQLQueryServer
import json

server = MCPSQLQueryServer()

# Create a table
server.handle_tool_call("create_table", {
    "table_name": "users",
    "columns": [
        {"name": "id", "type": "INTEGER", "primary_key": True},
        {"name": "name", "type": "TEXT", "not_null": True},
        {"name": "email", "type": "TEXT", "unique": True}
    ]
})

# Insert rows
server.handle_tool_call("insert_row", {
    "table_name": "users",
    "data": {"name": "Alice", "email": "alice@example.com"}
})

# Query
result = server.handle_tool_call("select_rows", {
    "table_name": "users",
    "where": "name = 'Alice'"
})

# Export
server.handle_tool_call("export_csv", {"table_name": "users"})

MCP Tool Reference

Tool Description Required Params
execute_sql Raw SQL execution sql
execute_batch Transactional batch statements
list_tables List all tables
table_schema Column/types/indexes table_name
create_table Create with columns table_name, columns
insert_row Insert one row table_name, data
insert_batch Insert multiple table_name, rows
select_rows SELECT with WHERE/LIMIT table_name
update_rows UPDATE with WHERE table_name, set_values, where
delete_rows DELETE with WHERE table_name, where
export_json Export as JSON table_name
export_csv Export as CSV table_name
database_info DB metadata

Tests

python -m pytest tests/ -v  # 33 tests, all passing

License

MIT

Author

AMEOBIUS — github.com/AMEOBIUS

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