iflow-mcp_netanelbollag-simple-psql-mcp

# Simple PostgreSQL MCP Server 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** - `execute_query` - Run SQL queries against your database - `test_connection` - Verify the database connection is working 2. **Resources** - `db://tables` - List of all tables in the schema - `db://tables/{table_name}` - 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](https://github.com/astral-sh/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 ``` >…