AnalyticDB PostgreSQL MCP Server

AnalyticDB PostgreSQL MCP Server serves as a universal interface between AI Agents and AnalyticDB PostgreSQL databases. It enables seamless communication between AI Agents and AnalyticDB PostgreSQL, helping AI Agents retrieve database metadata and execute SQL operations.

Configuration

Mode 1: Download

Download from Github

git clone https://github.com/aliyun/alibabacloud-adbpg-mcp-server.git

MCP Integration

Add the following configuration to the MCP client configuration file:

"mcpServers": {
  "adbpg-mcp-server": {
    "command": "uv",
    "args": [
      "--directory",
      "/path/to/adbpg-mcp-server",
      "run",
      "adbpg-mcp-server"
    ],
    "env": {
      "ADBPG_HOST": "host",
      "ADBPG_PORT": "port",
      "ADBPG_USER": "username",
      "ADBPG_PASSWORD": "password",
      "ADBPG_DATABASE": "database"
    }
  }
}

Mode 2: Using pip

pip install adbpg_mcp_server

MCP Integration

"mcpServers": {
  "adbpg-mcp-server": {
    "command": "uvx",
    "args": [
      "adbpg_mcp_server"
    ],
    "env": {
      "ADBPG_HOST": "host",
      "ADBPG_PORT": "port",
      "ADBPG_USER": "username",
      "ADBPG_PASSWORD": "password",
      "ADBPG_DATABASE": "database"
    }
  }
}

Components

Tools

• execute_select_sql: Execute SELECT SQL queries on the AnalyticDB PostgreSQL server
• execute_dml_sql: Execute DML (INSERT, UPDATE, DELETE) SQL queries on the AnalyticDB PostgreSQL server
• execute_ddl_sql: Execute DDL (CREATE, ALTER, DROP) SQL queries on the AnalyticDB PostgreSQL server
• analyze_table: Collect table statistics
• explain_query: Get query execution plan

Resources

Built-in Resources

• adbpg:///schemas: Get all schemas in the database

Resource Templates

• adbpg:///{schema}/tables: List all tables in a specific schema
• adbpg:///{schema}/{table}/ddl: Get table DDL
• adbpg:///{schema}/{table}/statistics: Show table statistics

Environment Variables

MCP Server requires the following environment variables to connect to AnalyticDB PostgreSQL instance:

• ADBPG_HOST: Database host address
• ADBPG_PORT: Database port
• ADBPG_USER: Database username
• ADBPG_PASSWORD: Database password
• ADBPG_DATABASE: Database name

Dependencies

• Python 3.10 or higher
• Required packages:
  • mcp >= 1.4.0
  • psycopg >= 3.1.0
  • python-dotenv >= 1.0.0
  • pydantic >= 2.0.0

Running

# Create and activate virtual environment
uv venv .venv
source .venv/bin/activate  # Linux/Mac
# or
.venv\Scripts\activate     # Windows

# Install dependencies
uv pip install -e .

# Run server
uv run adbpg-mcp-server