MCP PostgreSQL Demo
About
A FastMCP server that enables LLMs to connect and interact with PostgreSQL databases. It demonstrates how to use the Model Context Protocol (MCP) to allow Language Models to query and explore database schemas and tables.
Details
- Author
- Tibiritabara
- GitHub stars
- 7
- Downloads
- 197
- Categories
- Database
Jump to
- Schema Exploration: Retrieve metadata about database schemas
- Table Inspection: Get detailed information about table structures
- Database Querying: Execute SQL SELECT queries against the database
- YAML Formatting: Results returned in YAML format for LLM consumption
- Predefined prompts for schema, table descriptions, and data queries
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
MCP PostgreSQL DemoCommand (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
From the repository
Install Python 3.12+, PostgreSQL, and UV. Clone the repository, create a virtual environment, install dependencies with uv sync, and configure environment variables. Uncomment the run function in src/main.py and start the server with python -m src.main. Alternatively, use Docker with the provided Dockerfile. For client applications, add the MCP configuration to the client’s MCP config file (e.g., .cursor/mcp.json).
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"mcp postgresql demo": {
"postgres-mcp-tibiritabara": {
"command": "python",
"args": [
"-m",
"venv",
".venv"
]
}
}
}
}
McpServers
{
"postgres-mcp-tibiritabara": {
"command": "python",
"args": [
"-m",
"venv",
".venv"
]
}
}
MCP PostgreSQL Demo
A FastMCP server that enables LLMs to connect and interact with PostgreSQL databases. This project demonstrates how to use the Model Context Protocol (MCP) to allow Language Models to query and explore database schemas and tables.
Features
- Schema Exploration: Retrieve metadata about database schemas
- Table Inspection: Get detailed information about table structures
- Database Querying: Execute SQL queries against the database
- YAML Formatting: Results are returned in YAML format for easy consumption by LLMs
Resources
The server exposes the following MCP resources:
- database://{schema} - Get information about all tables in a schema
- database://{schema}/tables/{table} - Get detailed information about a specific table
Tools
- query_database - Execute SQL queries against the database (SELECT queries only)
Prompts
The server includes the following predefined prompts:
- prompt_schema_description - Ask for a description of a database schema
- prompt_table_description - Ask for a description of a specific table
- prompt_query_database - Ask for data from a specific table
Prerequisites
- Python 3.12 or higher
- PostgreSQL database
- UV package manager (recommended)
Installation
1. Clone the repository:
git clone <repository-url>
cd mcp-demo
2. Create a virtual environment:
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
3. Install UV (if not already installed):
pip install uv
4. Install dependencies with UV:
uv sync
5. Configure environment variables:
- Copy .env.example to .env
- Update the values according to your PostgreSQL configuration
Configuration
The application is configured using environment variables:
| Variable | Description | Default |
| ----------- | ------------------------ | --------- |
| APP_NAME | Application name | mcp-demo |
| DB_HOST | PostgreSQL host | localhost |
| DB_PORT | PostgreSQL port | 5432 |
| DB_USER | PostgreSQL username | postgres |
| DB_PASSWORD | PostgreSQL password | postgres |
| DB_NAME | PostgreSQL database name | postgres |
Usage
1. First, uncomment the run function in src/main.py by removing the comment from these lines at the bottom of the file:
# if __name__ == "__main__":
# print("Starting FastMCP server...")
# mcp.run()
2. Start the FastMCP server:
python -m src.main
3. The server will be available for LLMs to connect to and query your PostgreSQL database. With the server running, the MCP can be loaded into client applications for interaction.
Client Configuration
To use this MCP in a client application, add the following configuration to your client's MCP configuration file (e.g., .cursor/mcp.json):
{
"mcpServers": {
"postgres-mcp-server": {
"command": "/path/to/your/venv/bin/mcp",
"args": ["run", "/path/to/your/postgres-mcp/src/main.py"],
"env": {
"APP_NAME": "mcp-demo",
"DB_HOST": "localhost",
"DB_PORT": "5432",
"DB_USER": "postgres",
"DB_PASSWORD": "postgres",
"DB_NAME": "postgres"
}
}
}
}
Be sure to replace the paths with the actual paths to your virtual environment and project directory, and update the environment variables to match your PostgreSQL configuration.
Development
Install development dependencies with UV:
uv pip install -e ".[dev]"
Development tools included:
- JupyterLab for notebooks
- Pyright for type checking
- Ruff for linting
Docker
To run the application with Docker:
1. Build the Docker image:
docker build -t mcp-demo .
2. Run the container:
docker run --env-file .env.docker -p 8000:8000 mcp-demo
Example Usage
Get Schema Information
from mcp.client import get_client
client = get_client("http://localhost:8000")
schema_info = client.get_resource("database://public")
print(schema_info)
Get Table Details
table_info = client.get_resource("database://public/tables/users")
print(table_info)
Execute a Query
result = client.invoke_tool("query_database", {"query": "SELECT * FROM users LIMIT 10"})
print(result)
License
[Add your license information here]
Contributors
- Ricardo Santos <ricardo.santos.diaz@gmail.com>
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