Skip to main content
Glama
AutoMCP-SQL

AutoMCP-SQL

by Mav977

AutoMCP-SQL — Zero-Knowledge MCP Server

An MCP server that autonomously scans any SQLite database, generates typed CRUD tools for every table it discovers, builds a schema-aware prompt explaining joins/relationships, and enforces Zero-Knowledge security — the LLM never writes raw SQL, only calls pre-validated parameterized templates.


What It Does

Feature

Detail

Auto-Discovery

Scans sqlite_master at startup; no manual table registration

CRUD Generation

Creates get_, create_, update_, delete_ tools per table in memory

Schema Prompt

Injects table columns + foreign-key relationships as MCP instructions

Zero-Knowledge SQL

Instead of allowing the LLM to write arbitrary SQL (which risks SQL injection and destructive operations), the server generates isolated CRUD tools (Create, Read, Update, Delete) in memory for each table. The LLM interacts with these safe, pre-validated python templates

Configurable DB

Point at any SQLite file via DB_PATH env var


Related MCP server: Manual SQLite MCP Server

Project Structure

AutoMCP-SQL/
├── server.py        # MCP server — scans DB, generates tools, starts server
├── setupdb.py       # One-time script to create and seed legacy.db for testing
├── legacy.db        # SQLite database (auto-created by setupdb.py)
├── pyproject.toml   # Dependencies managed by uv
├── uv.lock          # Lockfile — guarantees reproducible installs
└── README.md

Tech Stack

Tool

Why

FastMCP

Minimal decorator-based MCP server; zero boilerplate for tool registration

sqlite3 (stdlib)

No extra dependency; sufficient for parameterized CRUD on any SQLite file

uv

10-100× faster than pip; lockfile guarantees reproducible installs across machines

MCP (Model Context Protocol)

Standard protocol for giving LLMs structured, auditable tool access


Prerequisites

  • Python 3.11+

  • uv — fast Python package/project manager

  • Claude Desktop — to connect the MCP server (optional)

Install uv if you don't have it:

# macOS / Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows (PowerShell)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Setup

1. Clone the repository

git clone https://github.com/Mav977/AutoMCP-SQL.git
cd AutoMCP-SQL

2. Install dependencies

uv sync

This reads uv.lock and recreates the exact virtual environment.

3. Seed the demo database

uv run setupdb.py

This creates legacy.db in the project root with sample tables (users, orders, products, etc.) so you can test immediately.

Using your own database? Skip this step and point DB_PATH at your existing .db file (see Configuration below).


Example: Claude Desktop Configuration

You can access the configuration file directly from within the app:

  1. Open Claude Desktop.

  2. Navigate to Settings.

  3. Select the Developer tab.

  4. Click Edit Config to open the claude_desktop_config.json file in your default text editor.

2. Add the MCP server entry

Replace the path below with the absolute path to your cloned server.py:

Windows:

{
  "mcpServers": {
    "AutoMCP-SQL": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "C:\\Users\\YourName\\Desktop\\Projects\\AutoMCP-SQL\\server.py"
      ],
      "env": {
        "DB_PATH": "C:\\Users\\YourName\\Desktop\\Projects\\AutoMCP-SQL\\legacy.db"
      }
    }
  }
}

macOS / Linux:

{
  "mcpServers": {
    "AutoMCP-SQL": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "mcp[cli]",
        "mcp",
        "run",
        "/home/yourname/projects/AutoMCP-SQL/server.py"
      ],
      "env": {
        "DB_PATH": "/home/yourname/projects/AutoMCP-SQL/legacy.db"
      }
    }
  }
}

Important: Use double backslashes (\\) in Windows paths inside JSON.

3. Restart Claude Desktop

Fully quit and reopen Claude Desktop. The MCP server starts automatically when Claude launches.

4. Verify the connection

Open a new conversation in Claude Desktop. Click the plus icon (+) in the chat input area, select Connectors, and then click Manage connectors. Here, you will see AutoMCP-SQL listed along with all the tools the MCP has access to (like get_users, create_orders, etc.).

You can also just ask Claude:

"What tables do you have access to?"

Claude will use the injected schema prompt to describe the database structure without querying it.


Using Your Own Database

Set DB_PATH in the config to point at any existing SQLite file:

"env": {
  "DB_PATH": "C:\\path\\to\\your\\database.db"
}

The server will scan it on startup and auto-generate tools for every table it finds — no code changes needed.


Configuration

Environment Variable

Default

Description

DB_PATH

./legacy.db (next to server.py)

Path to the SQLite database file


How Zero-Knowledge Security Works

The server never exposes raw SQL execution to the LLM. Instead:

  1. On startup, scan_db() reads the schema and builds a natural-language prompt describing tables and relationships.

  2. For each table, four tool functions are registered with hard-coded SQL templates:

    • get_<table> → SELECT * FROM <table> WHERE col = ?

    • create_<table> → INSERT INTO <table> (cols) VALUES (?)

    • update_<table> → UPDATE <table> SET col = ? WHERE id = ?

    • delete_<table> → DELETE FROM <table> WHERE id = ?

  3. All values are passed as parameterized arguments — never string-interpolated into queries.

  4. Claude can only call these named tools; it has no mechanism to execute arbitrary SQL.

This means even a prompt-injected or jailbroken model cannot run DROP TABLE or exfiltrate data via UNION — the attack surface is limited to the four CRUD templates.

Troubleshooting

Server doesn't appear in Claude Desktop

  • Wait a few seconds; it may take some time to load.

  • Double-check the path in claude_desktop_config.json — it must be the absolute path to server.py, not a folder.

  • Make sure uv is on your system PATH (open a new terminal and run uv --version to verify).

  • Fully quit Claude Desktop (system tray on Windows, Cmd+Q on Mac) and reopen it.

DB_PATH does not exist error Run uv run setupdb.py first to create legacy.db, or update DB_PATH in the config to point at an existing database.

Tools not showing up after config change Claude Desktop only reads the config on launch. Fully restart it after any config edits.

Available Tools

12 tools
create_ordersA

Insert a new row into orders. data = JSON string like '{"col":"val"}'.

Inputs: data (required). Returns: result

create_productsA

Insert a new row into products. data = JSON string like '{"col":"val"}'.

Inputs: data (required). Returns: result

create_usersA

Insert a new row into users. data = JSON string like '{"col":"val"}'.

Inputs: data (required). Returns: result

delete_ordersB

Delete a row from orders by id.

Inputs: row_id (required). Returns: result

delete_productsA

Delete a row from products by id.

Inputs: row_id (required). Returns: result

delete_usersB

Delete a row from users by id.

Inputs: row_id (required). Returns: result

get_ordersA

Get rows from orders. filters = JSON string like '{"col":"val"}' or empty string for all rows.

Inputs: filters. Returns: result

get_productsA

Get rows from products. filters = JSON string like '{"col":"val"}' or empty string for all rows.

Inputs: filters. Returns: result

get_usersA

Get rows from users. filters = JSON string like '{"col":"val"}' or empty string for all rows.

Inputs: filters. Returns: result

update_ordersA

Update a row in orders by id. data = JSON string of fields to update.

Inputs: data (required), row_id (required). Returns: result

update_productsA

Update a row in products by id. data = JSON string of fields to update.

Inputs: data (required), row_id (required). Returns: result

update_usersA

Update a row in users by id. data = JSON string of fields to update.

Inputs: data (required), row_id (required). Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A4/5.0

    Scored across 12 tools

    Disambiguation5/5

    Each tool is uniquely named with a verb (get, create, update, delete) and a specific table (users, products, orders). There is no overlap because every combination of action and table is distinct and clearly indicated by the name.

    Naming Consistency5/5

    All tool names follow the same verb_noun pattern using snake_case (e.g., get_users, update_products). This is perfectly consistent across the entire set, making the tools predictable and easy to navigate.

    Tool Count5/5

    With 12 tools, the count is well-scoped for a CRUD API covering three tables (users, products, orders). Each tool serves a clear purpose, and there is no bloat or redundancy.

    Completeness5/5

    Each of the three tables has complete CRUD coverage: get (read with optional filters), create (insert), update, and delete. This covers all standard lifecycle operations for a SQL-based server, leaving no obvious dead ends.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

    Related MCP Connectors

    Related MCP Servers

    • A
      license
      Not graded
      quality
      D
      maintenance
      Enables LLM agents to perform complete database operations on SQLite databases, including creating tables, executing queries, and managing data through CRUD operations with schema inspection capabilities.
      26 npm
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Enables direct interaction with a SQLite database through custom-mapped tools for creating and retrieving items. It provides structured, AI-optimized responses and manual control over database operations without requiring external API dependencies.
      -
    • A
      license
      B
      quality
      D
      maintenance
      Enables AI agents to interact with local SQLite databases with full CRUD, schema introspection, foreign key relations, generated columns, and multi-format import/export (CSV, JSON, XLSX) through natural language.
      26
      14 npm
      MIT