MCP PostgreSQL Query Agent

A read-only natural-language database agent built with FastMCP, LangChain, SQLAlchemy, and PostgreSQL. The MCP server exposes schema-discovery and SELECT tools, while the LangChain client decides which tools to call, generates SQL, and turns the result into a natural-language answer.

What it demonstrates

• Serving database capabilities as MCP tools

• Discovering tables, columns, and foreign-key relationships

• Translating natural-language questions into SQL

• Answering questions that require joins across related tables

• Restricting the exposed query tool to a single read-only SELECT

• Connecting LangChain agents to a streamable HTTP MCP server

Related MCP server: MCP PostgreSQL

Architecture

User question
     │
     ▼
LangChain agent + OpenRouter model
     │
     ▼
MCP client (streamable HTTP)
     │
     ▼
FastMCP server
 ├── list_tables
 ├── describe_table
 └── run_select
     │
     ▼
PostgreSQL

Project structure

.
├── hw_db.py           # Shared SQLAlchemy connection setup
├── hw_db_seed.py      # Demo schema and sample data
├── hw_db_server.py    # FastMCP database server
├── hw_db_client.py    # LangChain MCP client and agent
├── docker-compose.yml # Local PostgreSQL service
├── .env.example       # Required environment variables
└── pyproject.toml

Requirements

• Python 3.11+

• Docker, or an existing PostgreSQL instance

• An OpenRouter API key

Setup

Clone the repository and enter the project directory:

git clone https://github.com/YOUR_USERNAME/mcp-postgres-query-agent.git
cd mcp-postgres-query-agent

Create the environment file:

cp .env.example .env

Add your OpenRouter key to .env:

PG_DSN=postgresql+psycopg://postgres:postgres@localhost:5432/mcp_demo
OPENROUTER_API_KEY=your_openrouter_api_key

Install the dependencies with uv:

uv sync

Or with pip:

python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Run locally

Start PostgreSQL:

docker compose up -d

Create and seed the demo tables:

python hw_db_seed.py

Start the MCP server in one terminal:

python hw_db_server.py

Run the client in another terminal:

python hw_db_client.py

You can also pass a custom question:

python hw_db_client.py "Which department has the highest average salary?"

MCP tools

Demo schema

The seed script creates two related tables:

• departments: department name and location

• employees: employee name, salary, country, and department reference

The default question requires the agent to inspect both schemas and join the tables before answering.

Safety notes

The MCP query tool rejects non-SELECT statements and multiple SQL statements. This is a useful application-level guard, but it is not a complete database security boundary. For real deployments, connect with a PostgreSQL role that has read-only permissions and access only to the intended schemas.

Possible extensions

• Add a dedicated read-only PostgreSQL role

• Validate generated SQL with a parser instead of prefix checks

• Add query timeouts and row-level access controls

• Support multiple databases through separate MCP servers

• Add tracing and evaluation for generated SQL accuracy

License

This project is available under the MIT License.