amazon-datazone

The Amazon DataZone MCP Server provides a standardized MCP interface to interact with AWS DataZone resources. It exposes tools for domain, project, data management, glossary, and environment operations, enabling programmatic control via MCP clients. After starting the server, clients communicate over standard IO transport, making it suitable for local development or integration with chat assistants and automation pipelines. The server exposes 38 tools across five categories, including creating and listing domains, domain units, projects, assets, listings, data sources, subscriptions, glossaries, environments, connections, and blueprints, with rich parameter documentation available through your MCP client.

To use the server, first install and run it, then connect your MCP client to the stdio interface provided by the process. When integrating with clients like Claude Desktop or other MCP-enabled assistants, configure the client to launch the server process and communicate via the standard IO channel. The client configuration typically includes a name matching the server and a command to initiate the server process. You can then invoke any of the available tools by name, providing the required parameters as documented by the MCP client.

Prerequisites:

• Python 3.10 or later
• pip (Python package installer)
• AWS credentials configured (via AWS CLI, environment variables, or instance roles)

Installation steps:

1. Create and activate a Python virtual environment (optional but recommended): python -m venv venv source venv/bin/activate # on macOS/Linux venv\Scripts\activate # on Windows

2. Install the MCP server package from PyPI: pip install amazon-datazone-mcp-server

3. Verify installation by running the server in a test mode or via the normal startup command (the server is designed to listen on stdout for MCP clients): python -m amazon_datazone_mcp_server

4. If you use a containerized or restricted environment, ensure network access to AWS services and that Python dependencies are satisfied in the runtime environment.

Environment variables for AWS credentials can also be supplied through the AWS CLI or IAM roles when running on AWS infrastructure. The server uses the standard AWS credential resolution chain, so you can rely on AWS_DEFAULT_REGION, AWS_PROFILE, or instance profile credentials as needed. If you encounter connectivity issues, confirm that AWS permissions align with the needed DataZone operations. When deploying in production, enable robust logging and consider integrating with your existing observability stack. The server communicates over the MCP stdio transport, so ensure the MCP client is configured to launch and pipe to the server's standard input/output. If you need to customize startup, you can pass additional runtime parameters depending on the CLI exposed by the package.