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amazon-datazone-mcp-server

Official
by awslabs

create_project

Create a project in an Amazon DataZone domain by providing a domain ID and project name, with optional configuration for description, glossary terms, domain unit, and user parameters.

Instructions

Creates a new project in an Amazon DataZone domain.

Args: domain_identifier (str): The ID of the domain where the project will be created name (str): The name of the project (required) description (str, optional): The description of the project domain_unit_id (str, optional): The ID of the domain unit where the project will be created glossary_terms (List[str], optional): List of glossary terms that can be used in the project project_profile_id (str, optional): The ID of the project profile user_parameters (List[Dict[str, Any]], optional): The user parameters of the project

Returns: Any: The API response containing the created project details

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
descriptionNo
domain_unit_idNo
glossary_termsNo
user_parametersNo
domain_identifierYes
project_profile_idNo
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It only states that the tool creates a project and returns an API response, but fails to disclose side effects, permissions, or safety implications. For a mutation tool, this is minimal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear first sentence, a detailed Args list, and a Returns section. It is relatively concise, though the Args list is somewhat redundant with the schema. Still front-loaded and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and moderate complexity (7 parameters), the description is incomplete. It lacks details on naming conventions, uniqueness constraints, or asynchronous behavior. The return type is vague ('Any'). More context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the description compensates by listing all parameters with brief explanations in the 'Args' section. This adds basic meaning, but does not cover constraints or formats. It provides average clarity beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it creates a new project in an Amazon DataZone domain. It uses a specific verb and resource, and it distinguishes itself from sibling tools like create_project_membership and create_project_profile.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description lists arguments but does not provide explicit guidance on when to use this tool versus alternatives. It lacks context on prerequisites or when not to use, though the purpose is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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