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amazon-datazone-mcp-server

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From the repo.

Amazon DataZone MCP Server

Python Version License MCP

A high-performance Model Context Protocol (MCP) server that provides seamless integration with Amazon DataZone services. This server enables AI assistants and applications to interact with Amazon DataZone APIs through a standardized interface.

Features

  • Complete Amazon DataZone API Coverage: Access all major DataZone operations
  • Type Safety: Full type hints and validation
  • Production Ready: Robust error handling and logging
  • MCP Compatible: Works with any MCP-compatible client

Supported Operations

ModuleOperations
Domain ManagementCreate domains, manage domain units, search, policy grants
Project ManagementCreate/manage projects, project profiles, memberships
Data ManagementAssets, listings, subscriptions, form types, data sources
GlossaryBusiness glossaries, glossary terms
EnvironmentEnvironments, connections, blueprints

Installation

pip install amazon-datazone-mcp-server

Configuration

Configure AWS credentials using the standard AWS methods:

  • AWS CLI: aws configure
  • Environment variables: AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_DEFAULT_REGION
  • IAM roles or instance profiles

Running the Server

The server uses stdio transport for secure communication with MCP clients:

amazon-datazone-mcp-server

Integration with MCP Clients

Configure in your MCP client (e.g., Claude Desktop):

{
  "name": "amazon-datazone-mcp-server",
  "command": "amazon-datazone-mcp-server"
}

Available Tools

The server provides 38 tools across 5 categories:

Domain Management

  • get_domain, create_domain, list_domains
  • list_domain_units, create_domain_unit
  • add_entity_owner, add_policy_grant
  • search, search_types
  • User/group profile management

Project Management

  • create_project, get_project, list_projects
  • create_project_membership, list_project_memberships
  • Project profile management

Data Management

  • Asset operations: get_asset, create_asset, publish_asset
  • Listing operations: get_listing, search_listings
  • Data source management: create_data_source, start_data_source_run
  • Subscription management: request, accept, get subscriptions
  • Form type management

Glossary Management

  • create_glossary, get_glossary
  • create_glossary_term, get_glossary_term

Environment Management

  • Environment operations: list_environments, get_environment
  • Connection management: create_connection, get_connection, list_connections
  • Blueprint operations: list and get blueprints and configurations

Each tool includes comprehensive parameter documentation and examples accessible through your MCP client.

License

Licensed under the Apache License 2.0 - see the LICENSE file for details.

Disclaimer

This is an unofficial, community-developed project and is not affiliated with, endorsed by, or supported by Amazon Web Services, Inc.

  • AWS and DataZone are trademarks of Amazon.com, Inc. or its affiliates
  • Users are responsible for their own AWS credentials, costs, and compliance
  • No warranty or support is provided - use at your own risk
  • Always follow AWS security best practices

For official Amazon DataZone documentation, visit Amazon DataZone Documentation.

Collected info

  • ★ 6 stars
  • ⎇ 5 forks
  • Language: Python
  • Source updated: 2/5/2026

Config for your environment

Replace {MCP_ENDPOINT_URL} with this MCP’s endpoint URL (from its repo or docs above). No API key — you connect directly.

Tool

OS

Config file: ~/.cursor/mcp.json

{
  "mcpServers": {
    "mcp-server": {
      "url": "{MCP_ENDPOINT_URL}"
    }
  }
}

Paste into mcpServers in the config file. Restart Cursor after saving.

If this MCP is also published on mcpchannel.ai, you can subscribe from Browse and use the gateway config there instead.