Which integrations are available for this server?

Exposes SQLite databases to AI agents, enabling the execution of SQL statements, schema inspection, and retrieval of table metadata including columns, indexes, and foreign keys.

How do I use sqlite-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@sqlite-mcp Show me the schema and row count for the users table" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

sqlite-mcp

An MCP (Model Context Protocol) server that exposes SQLite databases as tools for AI agents. Connect any SQLite database and let LLMs query schemas, run SQL, and inspect tables through a standardized interface.

Features

execute_sql — Run arbitrary SQL statements with support for dry-run mode (EXPLAIN QUERY PLAN), automatic result truncation, and configurable row limits.
get_table_info — Retrieve complete table metadata in a single call: columns, types, DDL, indexes, foreign keys, and row count.
Read-only mode — Optionally block all write operations for safe, production-friendly access.
Query timeout — Configurable per-query timeout to prevent runaway queries.

Requirements

Python 3.11+
uv (recommended) or pip

Installation

# Clone the repository
git clone https://github.com/<owner>/sqlite-mcp.git
cd sqlite-mcp

# Install with uv
uv sync

Or with pip:

pip install .

Usage

Environment Variables

Variable	Required	Default	Description
`SQLITE_DB_PATH`	Yes	—	Path to the SQLite database file
`SQLITE_READ_ONLY`	No	`false`	Set to `true` to disable write operations
`SQLITE_TIMEOUT`	No	`30`	Query timeout in seconds

Running the Server

SQLITE_DB_PATH=./my_database.db sqlite-mcp

The server communicates over stdio and is designed to be launched by an MCP-compatible client (e.g., Cursor, Claude Desktop).

MCP Client Configuration

Add the server to your MCP client config (e.g., .cursor/mcp.json):

{
  "mcpServers": {
    "sqlite": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/sqlite-mcp", "sqlite-mcp"],
      "env": {
        "SQLITE_DB_PATH": "/path/to/database.db",
        "SQLITE_READ_ONLY": "true"
      }
    }
  }
}

Tools

`execute_sql`

Execute a SQL statement against the connected database.

Parameter	Type	Default	Description
`sql`	`str`	—	The SQL statement to execute
`dry_run`	`bool`	`false`	Return the query plan instead of executing
`max_rows`	`int`	`100`	Maximum rows to return

Example response (SELECT):

{
  "results": [{"id": 1, "name": "Alice"}],
  "row_count": 1,
  "truncated": false
}

Example response (dry run):

{
  "query_plan": [{"id": 0, "parent": 0, "detail": "SCAN users"}]
}

`get_table_info`

Get complete schema and metadata for a table.

Parameter	Type	Description
`table`	`str`	The table name to inspect

Example response:

{
  "table": "users",
  "columns": [
    {"name": "id", "type": "INTEGER", "nullable": false, "default": null, "primary_key": true},
    {"name": "name", "type": "TEXT", "nullable": true, "default": null, "primary_key": false}
  ],
  "ddl": "CREATE TABLE users (id INTEGER PRIMARY KEY, name TEXT)",
  "indexes": [],
  "foreign_keys": [],
  "row_count": 42
}