Oceanbase Mcp Server

What is Oceanbase Mcp Server about?

Enables AI assistants to interact with OceanBase databases in a controlled manner, allowing operations such as listing tables, reading table contents, and executing arbitrary SQL queries while enforcing security and logging.

How to use Oceanbase Mcp Server?

1. Installation – Install the package with pip install oceanbase-mcp-server or install development dependencies via pip install -r requirements.txt.
2. Configuration – Set required environment variables: OB_HOST, OB_PORT (optional, defaults to 2881), OB_USER, OB_PASSWORD, and OB_DATABASE.
3. Running the server – Start the MCP server with python -m oceanbase_mcp_server. For Claude Desktop, configure claude_desktop_config.json to invoke the server using the uv command as shown in the README.
4. Interaction – AI assistants send Model Context Protocol requests to the running server to perform database operations.

Key Features

• List available OceanBase tables as resources
• Read table contents with pagination support
• Execute arbitrary SQL queries with robust error handling
• Secure credential handling via environment variables
• Comprehensive operation logging for auditability
• Easy integration with Claude Desktop and other MCP‑compatible clients

Use Cases

• Data exploration for AI agents that need to discover schema and sample rows before analysis.
• Report generation where an assistant runs aggregation queries and formats results for end‑users.
• Automated monitoring by allowing AI to fetch metrics stored in database tables.
• Secure data retrieval in chat‑bots that must respect least‑privilege database access.

FAQ

Q: Do I need a special database user? A: Yes, create a dedicated OceanBase user with only the permissions required for the intended operations (e.g., SELECT, limited UPDATE).

Q: How are credentials protected? A: Credentials are supplied via environment variables and never stored in the code repository.

Q: Can I limit which queries are allowed? A: The server can be extended with query whitelisting or custom validation logic before execution.

Q: What logging is provided? A: All database interactions, including query text and execution outcome, are logged to aid auditing and debugging.

Q: Is there a Docker image? A: The repository does not include an official Docker image, but the server can be containerized using a standard Python base image.

OceanBase MCP Server

A Model Context Protocol (MCP) server that enables secure interaction with OceanBase databases. This server allows AI assistants to list tables, read data, and execute SQL queries through a controlled interface, making database exploration and analysis safer and more structured.

Features

• List available OceanBase tables as resources
• Read table contents
• Execute SQL queries with proper error handling
• Secure database access through environment variables
• Comprehensive logging

Installation

pip install oceanbase-mcp-server

Configuration

Set the following environment variables:

OB_HOST=localhost     # Database host
OB_PORT=2881         # Optional: Database port (defaults to 2881 if not specified)
OB_USER=your_username
OB_PASSWORD=your_password
OB_DATABASE=your_database

Usage

With Claude Desktop

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "oceanbase": {
      "command": "uv",
      "args": [
        "--directory", 
        "path/to/oceanbase_mcp_server",
        "run",
        "oceanbase_mcp_server"
      ],
      "env": {
        "OB_HOST": "localhost",
        "OB_PORT": "2881",
        "OB_USER": "your_username",
        "OB_PASSWORD": "your_password",
        "OB_DATABASE": "your_database"
      }
    }
  }
}

As a standalone server

# Install dependencies
pip install -r requirements.txt

# Run the server
python -m oceanbase_mcp_server

Development

# Clone the repository
git clone https://github.com/yourusername/oceanbase_mcp_server.git
cd oceanbase_mcp_server

# Create virtual environment
python -m venv venv
source venv/bin/activate  # or `venv\Scripts\activate` on Windows

# Install development dependencies
pip install -r requirements-dev.txt

# Run tests
pytest

Security Considerations

• Never commit environment variables or credentials
• Use a database user with minimal required permissions
• Consider implementing query whitelisting for production use
• Monitor and log all database operations

Security Best Practices

This MCP server requires database access to function. For security:

1. Create a dedicated OceanBase user with minimal permissions
2. Never use root credentials or administrative accounts
3. Restrict database access to only necessary operations
4. Enable logging for audit purposes
5. Regular security reviews of database access

See OceanBase Security Configuration Guide for detailed instructions on:

• Creating a restricted OceanBase user
• Setting appropriate permissions
• Monitoring database access
• Security best practices

⚠️ IMPORTANT: Always follow the principle of least privilege when configuring database access.

License

Apache License - see LICENSE file for details.

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request