PostgreSQL Model Context Protocol (PG-MCP) Server

by tanster1234

194 downloads

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GitHub

Database

Description

# PostgreSQL Model Context Protocol (PG-MCP) Server A Model Context Protocol (MCP) server for PostgreSQL databases with enhanced capabilities for AI agents. ## Overview PG-MCP is a server implementation of the [Model Context Protocol](https://modelcontextprotocol.io) for…

About

Details

Author: tanster1234
Downloads: 194
Categories: Database

- Multi-database support with simultaneous connections.
- Rich catalog information from table/column descriptions.
- Query execution plan analysis via pg_explain tool.
- Built-in extension context for PostGIS and pgvector.
- Read-only mode enforced via transaction settings.
- Connection pooling and secure opaque connection IDs.

Setting up with Highlight

This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:

Download and install Highlight from highlightai.com/download
Navigate to the plugins tab and select "Add Custom Plugin"
Configure the plugin with the settings below

Plugin Name PostgreSQL Model Context Protocol (PG-MCP) Server

Command (node, npx, python, etc.)

Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
Enable "Start Automatically" if you want the plugin to start when Highlight launches

Setting up with Cursor

Open Cursor's settings
Navigate to the MCP section
Click "Add new Global MCP server"
Copy and paste the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

Setting up with Claude Desktop

Open Claude Desktop's settings
Go to the Integrations tab
Click "Add MCP Server"
Use the configuration below based on your operating system

Note: Make sure Claude Desktop is running before attempting to connect.

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

Setting up with Windsurf

Open Windsurf's preferences
Go to the Integrations section
Click "Add MCP Integration"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

Setting up with Cline

Open Cline's settings
Navigate to the Integrations section
Click "Add MCP Server"
Copy and paste the configuration below based on your operating system

Note: Make sure to restart Cline after adding the configuration.

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

Setting up with Goose

Open Goose's preferences
Go to the Integrations tab
Select "MCP Servers"
Click "Add New Server"
Use the configuration below based on your operating system

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

JSON

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

From the repository

Install via Docker or manual setup with Python 3.13+. Run python -m server.app after installing dependencies with uv sync --frozen. Clients connect to the SSE endpoint (default http://localhost:8000/sse) and invoke tools like connect, pg_query, and pg_explain using a secure connection ID.

Claude Desktop / Cursor

Paste into your MCP client config file to install this server.

{
    "mcpServers": {
        "postgresql model context protocol (pg-mcp) server": {
            "mcp_server_postgres": {
                "command": "python",
                "args": [
                    "-m",
                    "venv",
                    ".venv"
                ]
            }
        }
    }
}

McpServers

{
    "mcp_server_postgres": {
        "command": "python",
        "args": [
            "-m",
            "venv",
            ".venv"
        ]
    }
}

PostgreSQL Model Context Protocol (PG-MCP) Server

A Model Context Protocol (MCP) server for PostgreSQL databases with enhanced capabilities for AI agents.

Overview

PG-MCP is a server implementation of the Model Context Protocol for PostgreSQL databases. It provides a comprehensive API for AI agents to discover, connect to, query, and understand PostgreSQL databases through MCP's resource-oriented architecture.

This implementation builds upon and extends the reference Postgres MCP implementation with several key enhancements:

1. Full Server Implementation: Built as a complete server with SSE transport for production use
2. Multi-database Support: Connect to multiple PostgreSQL databases simultaneously
3. Rich Catalog Information: Extracts and exposes table/column descriptions from the database catalog
4. Extension Context: Provides detailed YAML-based knowledge about PostgreSQL extensions like PostGIS and pgvector
5. Query Explanation: Includes a dedicated tool for analyzing query execution plans
6. Robust Connection Management: Proper lifecycle for database connections with secure connection ID handling

Features

Connection Management

- Connect Tool: Register PostgreSQL connection strings and get a secure connection ID
- Disconnect Tool: Explicitly close database connections when done
- Connection Pooling: Efficient connection management with pooling

Query Tools

- pg_query: Execute read-only SQL queries using a connection ID
- pg_explain: Analyze query execution plans in JSON format

Schema Discovery Resources

- List schemas with descriptions
- List tables with descriptions and row counts
- Get column details with data types and descriptions
- View table constraints and indexes
- Explore database extensions

Data Access Resources

- Sample table data (with pagination)
- Get approximate row counts

Extension Context

Built-in contextual information for PostgreSQL extensions like:

- PostGIS: Spatial data types, functions, and examples
- pgvector: Vector similarity search functions and best practices

Additional extensions can be easily added via YAML config files.

Installation

Prerequisites

- Python 3.13+
- PostgreSQL database(s)

Using Docker

```bash

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Description

About

Details

Jump to

Setting up with Highlight

From the repository

Claude Desktop / Cursor

McpServers

PostgreSQL Model Context Protocol (PG-MCP) Server

Overview

Features

Connection Management

Query Tools

Schema Discovery Resources

Data Access Resources

Extension Context

Installation

Prerequisites

Using Docker

Install

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