NetanelBollag/simple-psql-mcp

This is a template project for those looking to build their own MCP servers. I designed it to be dead simple to understand and adapt - the code is straightforward with MCP docs attached so you can quickly get up to speed.
## What is MCP?
TL;DR - It's a way to write plugins for AI
Model Context Protocol (MCP) is a standard way for LLMs to interact with external tools and data. In a nutshell:
Tools allow the LLM to execute commands (like running a database query)
Resources are data you can attach to conversations (like attaching a file to a prompt)
Prompts are templates that generate consistent LLM instructions
## Features
This PostgreSQL MCP server implements:
1. Tools
executequery - Run SQL queries against your database
testconnection - Verify the database connection is working
2. Resources
db://tables - List of all tables in the schema
db://tables/{tablename} - Schema information for a specific table
db://schema - Complete schema information for all tables in the database
3. Prompts
Query generation templates
Analytical query builders
Based on the templates in this repo
## Prerequisites
Python 3.8+
uv - Modern Python package manager and installer
npx (included with Node.js)
PostgreSQL database you can connect to
## Quick Setup
1. Create a virtual environment and install dependencies:
bash
# Create a virtual environment with uv
uv venv
# Activate the virtual environment
source .venv/bin/activate # On Windows: .venv\Scripts\activate
# Install dependencies
uv pip install -r requirements.txt
2. Run the server with the MCP Inspector:
bash
# Replace with YOUR actual database credentials
npx @modelcontextprotocol/inspector uv --directory . run postgres -e DSN=postgresql://username:password@hostname:port/database -e SCHEMA=public
> Note: If this is your first time running npx, you'll be prompted to approve the installation. Type 'y' to proceed.
After running this command, you'll see the MCP Inspector interface launched in your browser. You should see a message like:
MCP Inspector is up and running at http://localhost:5173
If the browser doesn't open automatically, copy and paste the URL into your browser. You should see something like this:
3. Using the Inspector:
Click the "Connect" button in the interface (unless there's an error message in the console on the bottom left)
Explore the "Tools", "Resources", and "Prompts" tabs to see available functionality
Try clicking on listed commands or typing resource names to retrieve resources and prompts
The interface allows you to test queries and see how the MCP server responds
4. Take a look at the official docs
Official server developers guide: https://modelcontextprotocol.io/quickstart/server
More on the inspector: https://modelcontextprotocol.io/docs/tools/inspector
## Connect Your AI Tool to the Server
You can configure the MCP server for your AI assistant by creating an MCP configuration file:
json
"mcpServers": {
"postgres": {
"command": "/path/to/uv",
"args": [
"--directory",
"/path/to/simple-psql-mcp",
"run",
"postgres"
],
"env": {
"DSN": "postgresql://username:password@localhost:5432/my-db",