sql-mcp 0.3.0

Generic SQL database (Postgres, MySQL/MariaDB, MSSQL, Oracle, SQLite) API + MCP Server + A2A Server for Agentic AI!

Sql Mcp

API | MCP Server | A2A Agent

Generic SQL database API + MCP Server + A2A Agent for the agent-utilities ecosystem — one connector for PostgreSQL, MySQL/MariaDB, Microsoft SQL Server, Oracle, and SQLite over SQLAlchemy 2.x Core.

Version: 0.3.0

Documentation — Installation, deployment, and usage across the API, CLI, and MCP interfaces are maintained in docs/.

Table of Contents

• Overview
• What it provides
• MCP tools
• Dialects & extras
• Configuration (environment)
• Installation
• Usage
• MCP config
• Docker deployment
• Safety model
• Tests

Overview

sql-mcp exposes read-only queries, gated DML/DDL, schema reflection, and connection administration as typed, deterministic MCP tools, and ships an optional Pydantic-AI agent server. It is read-only by default: every query passes a statement-type allowlist, every result is bounded by a row cap and a timeout, and all values travel as bound parameters — never interpolated into SQL strings.

What it provides

• SqlApi (sql_mcp.api.api_client_sql) — a SQLAlchemy 2.x Core facade with named multi-connection support, lazy engine creation, the read-only statement gate, row-cap/timeout enforcement, and bounded result envelopes ({columns, rows, row_count, truncated}).
• Four MCP tools (sql-mcp console script): sql_query (execute/explain), sql_execute (execute/script — gated by SQL_ALLOW_WRITES), sql_schema (schemas/tables/views/columns/indexes/foreign_keys/ddl/sample), and sql_admin (ping/version/active_connections/connections/dialects). See docs/usage.md for the full action surface.
• A dialect registry (sql_mcp.dialects) — per-engine driver, URL scheme, pip extra, EXPLAIN prefix, and admin SQL. Core ships SQLite only; the other drivers install via extras.
• An A2A agent server (sql-agent console script) — a Pydantic-AI graph agent wired to the MCP server via MCP_URL.

MCP tools

Tool	Actions	Description
sql_query	execute, explain	Run a read-only SELECT/CTE with bound parameters, or return the dialect's query plan
sql_execute	execute, script	One DML/DDL statement (or an all-or-nothing statement list) in a transaction — requires SQL_ALLOW_WRITES=True
sql_schema	schemas, tables, views, columns, indexes, foreign_keys, ddl, sample	Reflect schemas, tables, columns, indexes, FKs, CREATE DDL, and preview rows
sql_admin	ping, version, active_connections, connections, dialects	Connection health, server version, server sessions, registry info, driver availability

Every tool takes action, params_json, and an optional connection naming one of the configured connections. The whole set is toggled with SQLTOOL.

Dialects & extras

Dialect	SQLAlchemy scheme	Driver	Install
SQLite	sqlite+pysqlite	stdlib	pip install sql-mcp (core)
PostgreSQL	postgresql+psycopg	psycopg 3	pip install sql-mcp[postgres]
MySQL / MariaDB	mysql+pymysql	PyMySQL	pip install sql-mcp[mysql]
SQL Server	mssql+pyodbc	pyodbc	pip install sql-mcp[mssql]
Oracle	oracle+oracledb	python-oracledb	pip install sql-mcp[oracle]

pip install sql-mcp[all] pulls every driver plus the MCP and agent extras.

Configuration (environment)

Var	Default	Meaning
SQL_CONNECTIONS	(empty)	JSON map of named connections: DSN strings or {dialect, host, port, username, password, database, options} objects
SQL_URL	(empty)	Single DSN registered as connection default
SQL_DIALECT / SQL_HOST / SQL_PORT / SQL_USERNAME / SQL_PASSWORD / SQL_DATABASE / SQL_OPTIONS	(empty)	Discrete fields for a single default connection
SQL_ALLOW_WRITES	False	Enable sql_execute (DML/DDL). Read-only by default
SQL_MAX_ROWS	500	Per-call row cap; tool requests are clamped to it
SQL_TIMEOUT_SECONDS	30	Per-statement timeout
SQLTOOL	True	Register the SQL tool set

With nothing configured the server registers a zero-infra in-memory SQLite connection named memory, so it works out of the box. Tools take an optional connection parameter naming one of the configured connections; it defaults to the sole/first one. Passwords are parsed into sqlalchemy.URL objects and only ever rendered redacted. Copy .env.example to .env and populate only what you use.

Installation

pip install sql-mcp            # core (SQLite, MCP server, API)
pip install sql-mcp[all]       # every driver + MCP + agent extras
pip install -e .               # from source

Or pull the container image:

docker pull knucklessg1/sql-mcp:latest

Usage

sql-mcp                        # stdio MCP server (default transport)
sql-mcp --transport streamable-http --host 0.0.0.0 --port 8000

Point it at a database:

export SQL_URL="postgresql+psycopg://svc:****@db.example.com:5432/app"
sql-mcp

Or several:

export SQL_CONNECTIONS='{
  "warehouse": "postgresql+psycopg://svc:****@dw.example.com:5432/dw",
  "erp": {"dialect": "mysql", "host": "erp.example.com", "username": "svc",
           "password": "****", "database": "erp"}
}'
sql-mcp

Run the agent server against a live MCP server:

sql-agent --mcp-url http://localhost:8000/mcp --host 0.0.0.0 --port 8080

MCP config

{
  "mcpServers": {
    "sql-mcp": {
      "command": "uv",
      "args": ["run", "sql-mcp"],
      "env": {
        "SQL_URL": "postgresql+psycopg://svc:****@db.example.com:5432/app",
        "SQL_ALLOW_WRITES": "False"
      }
    }
  }
}

Additional Deployment Options

sql-mcp can also run as a local container (Docker / Podman / uv) or be consumed from a remote deployment. The Deployment guide has full, copy-paste mcp_config.json for all four transports — stdio, streamable-http, local container / uv, and remote URL:

• Local container / uv — launch the server from mcp_config.json via uvx, docker run, or podman run, or point at a local streamable-http container by url.
• Remote URL — connect to a server deployed behind Caddy at http://sql-mcp.arpa/mcp using the "url" key.

Docker deployment

docker compose -f docker/mcp.compose.yml up -d      # MCP server only
docker compose -f docker/agent.compose.yml up -d    # MCP + A2A agent
curl -s http://localhost:8000/health                 # {"status":"OK"}

Both services read configuration from ../.env (copy .env.example); see docs/deployment.md.

Safety model

• Read-only by default — sql_execute refuses to run unless the server was started with SQL_ALLOW_WRITES=True; agents cannot flip the flag per call.
• Statement allowlist — sql_query accepts only SELECT/WITH/EXPLAIN/ SHOW/DESCRIBE/PRAGMA/VALUES; CTEs are inspected at paren depth zero so WITH ... INSERT cannot smuggle a write, SELECT INTO is rejected, and multi-statement payloads are refused.
• Bounded results — per-call row caps clamp to SQL_MAX_ROWS; statements run under SQL_TIMEOUT_SECONDS on a worker thread.
• Parameterized only — values bind via :name parameters; identifiers are quoted by SQLAlchemy reflection, never hand-interpolated.

Tests

python -m pytest          # full suite against in-memory SQLite (no live DBs)
pre-commit run --all-files