Amazon SageMaker Catalog Server
БесплатноНе проверенAuto-generates MCP tools for all Amazon DataZone API operations, enabling natural language management of SageMaker Catalog resources.
Описание
Auto-generates MCP tools for all Amazon DataZone API operations, enabling natural language management of SageMaker Catalog resources.
README
MCP server for Amazon SageMaker Catalog (DataZone) with 100% API coverage via auto-generation from the botocore service model.
This server automatically generates MCP tools for all 175+ DataZone API operations by reading the service model from botocore at startup. When AWS adds new operations, simply update boto3 — no code changes needed.
Features
- 100% API coverage: Every DataZone operation is exposed as an MCP tool
- Auto-updating: New operations appear automatically when boto3 is updated
- Compatible: Includes all tools from the official
awslabs/amazon-datazone-mcp-server, plus 126+ more - Dual transport: Supports stdio (local) and Streamable HTTP (remote)
- Standard AWS credentials: Uses the standard boto3 credential chain
- Correct parameter schemas: Each tool exposes the exact input schema from the AWS API (not a generic kwargs wrapper)
Installation
# From source
git clone https://github.com/difeorte/amazon-sagemaker-catalog-mcp-server.git
cd amazon-sagemaker-catalog-mcp-server
pip install .
# For development
pip install -e ".[dev]"
Prerequisites
AWS Credentials
The server uses the standard boto3 credential chain:
- Environment variables (
AWS_ACCESS_KEY_ID,AWS_SECRET_ACCESS_KEY) - AWS credentials file (
~/.aws/credentials) - AWS SSO config (
~/.aws/configwithsso_session) - Instance profile (EC2, ECS, Lambda)
IAM Permissions
The IAM role or user needs DataZone permissions. For a read-only catalog agent (browse, search, subscribe):
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"datazone:List*",
"datazone:Get*",
"datazone:Search*",
"datazone:CreateSubscriptionRequest"
],
"Resource": "*"
}
]
}
For full access (create/update/delete resources), use datazone:* — but scope it down based on your use case. The server exposes all 175+ operations, so the IAM policy is what controls what the agent can actually do.
SageMaker Unified Studio Domains
For catalog operations like search_listings, create_subscription_request, etc., the IAM role must be added as a project member in the SageMaker Unified Studio portal. This is a one-time setup per role per project. Without project membership, administrative operations (list_domains, get_domain, list_projects) still work, but catalog-level operations will return AccessDeniedException.
Environment Variables
| Variable | Description | Default |
|---|---|---|
AWS_REGION |
AWS region for API calls | boto3 default |
AWS_PROFILE |
AWS profile name | default |
MCP_TRANSPORT |
Transport type (stdio or streamable-http) |
stdio |
MCP_PORT |
Port for HTTP transport | 8000 |
Usage
With stdio (local, default)
sagemaker-catalog-mcp-server
With Streamable HTTP (remote)
sagemaker-catalog-mcp-server --transport streamable-http --port 8000
CLI Options
--transport {stdio,streamable-http} Transport type (default: stdio)
--port PORT Port for HTTP transport (default: 8000)
--region REGION AWS region
--profile PROFILE AWS profile name
MCP Client Configuration (Kiro, Claude Desktop, etc.)
Add to your MCP client configuration (e.g., .kiro/settings/mcp.json):
{
"mcpServers": {
"sagemaker-catalog": {
"command": "sagemaker-catalog-mcp-server",
"args": ["--region", "us-east-1"],
"env": {
"AWS_PROFILE": "your-profile"
}
}
}
}
Or if running from source without installing:
{
"mcpServers": {
"sagemaker-catalog": {
"command": "/path/to/project/.venv/bin/python",
"args": ["-m", "sagemaker_catalog_mcp_server"],
"env": {
"AWS_REGION": "us-east-1",
"AWS_PROFILE": "your-profile",
"PYTHONPATH": "/path/to/project/src"
}
}
}
}
Available Tools
The server exposes 175+ tools, one for each DataZone API operation. Examples:
| Tool | Description |
|---|---|
list_domains |
Lists Amazon DataZone domains |
get_domain |
Gets a domain |
create_project |
Creates a project |
search_listings |
Searches published assets in the catalog |
create_subscription_request |
Requests access to a data asset |
get_asset |
Gets asset details (technical + business metadata) |
create_glossary |
Creates a business glossary |
list_data_sources |
Lists data sources in a project |
For the complete list, start the server and use your MCP client's tool listing feature.
Important Considerations
Project membership setup — To add an IAM role as a project member programmatically, the data domain unit that owns the project must first have the "Add to project member pool" policy enabled by the domain unit owner. Without this policy, the API returns
AccessDeniedException. Currently, adding project members is done from the SageMaker Unified Studio portal.Tested on SageMaker Catalog — This server has been tested on SageMaker Catalog (which runs on Amazon DataZone). It has not been tested on standalone DataZone V1 domains.
Querying Subscribed Data
When a subscription is approved, SageMaker Unified Studio creates resource links in the consumer project's Lakehouse database (e.g., central_data_lake_<envId>). To query subscribed data, the agent must chain-assume the project execution role (datazone_usr_role_<projectId>_<envId>) and use the project's Athena workgroup. The data appears under the local Lakehouse database, not the producer's catalog ID.
Compatibility
This server is an unofficial extended version inspired by awslabs/amazon-datazone-mcp-server (v0.1.1). All 49 tools from the official server are available with the same names and parameters, plus 126+ additional tools covering the rest of the API.
Development
# Install dev dependencies
pip install -e ".[dev]"
# Run tests
pytest -v
Architecture
The server uses a code generation approach at startup:
- ServiceModelParser reads
service-2.jsonfrom botocore (supports.json.gz) - ToolGenerator creates MCP tool definitions with correct JSON Schema for each operation
- ToolExecutor executes operations against AWS via boto3 with response serialization
- Low-level MCP SDK (
mcp.server.lowlevel.Server) handles the protocol, ensuring each tool gets its exactinputSchemafrom the AWS API
This means the server automatically supports new API operations when boto3 is updated.
License
Apache 2.0
from github.com/difeorte/amazon-sagemaker-catalog-mcp-server
Установка Amazon SageMaker Catalog Server
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/difeorte/amazon-sagemaker-catalog-mcp-serverFAQ
Amazon SageMaker Catalog Server MCP бесплатный?
Да, Amazon SageMaker Catalog Server MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Amazon SageMaker Catalog Server?
Нет, Amazon SageMaker Catalog Server работает без API-ключей и переменных окружения.
Amazon SageMaker Catalog Server — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Amazon SageMaker Catalog Server в Claude Desktop, Claude Code или Cursor?
Открой Amazon SageMaker Catalog Server на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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