NetanelBollag simple psql mcp

WHAT IT CONNECTS

NetanelBollag simple psql mcp 为 AI Agent 提供什么

• **Tools**
• `execute_query` - Run SQL queries against your database
• `test_connection` - Verify the database connection is working
• **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
• **Prompts**
• Query generation templates
• Analytical query builders
• Based on the templates in this repo
• 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
• **Create a virtual environment and install dependencies:**
• **Run the server with the MCP Inspector:**
• **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
• **Take a look at the official docs**
• "What are all the tables in my database?"
• "Show me the top 5 users by creation date"
• "Count addresses by state"
• Create a new directory under `/src` (e.g., `/src/my-new-mcp`)
• Implement your MCP server following the PostgreSQL example
• Add your new MCP to `pyproject.toml`:
• MCP docs included for easy LLM development
• Based on the approach at: https://modelcontextprotocol.io/tutorials/building-mcp-with-llms