Skip to main content
Glama
awslabs

amazon-datazone-mcp-server

Official
by awslabs

create_glossary_term

Create a business glossary term in Amazon DataZone by providing domain and glossary identifiers, a name, and optional descriptions, status, and term relations.

Instructions

Creates a new business glossary term in Amazon DataZone.

Args: domain_identifier (str): The ID of the domain where the glossary term will be created Pattern: ^dzd[-][a-zA-Z0-9-]{1,36}$ glossary_identifier (str): The ID of the glossary where the term will be created Pattern: ^[a-zA-Z0-9_-]{1,36}$ name (str): The name of the glossary term (1-256 characters) short_description (str, optional): A short description of the term (0-1024 characters) long_description (str, optional): A detailed description of the term (0-4096 characters) status (str, optional): The status of the term (ENABLED or DISABLED, default: ENABLED) term_relations (Dict[str, List[str]], optional): The term relations Example: { "classifies": ["term-id-1", "term-id-2"], "isA": ["term-id-3"] } client_token (str, optional): A unique token to ensure idempotency (1-128 characters) Pattern: ^[\x21-\x7E]+$

Returns: Any: The API response containing the created glossary term details

Example: python response = await create_glossary_term( domain_identifier="dzd_123456789", glossary_identifier="gloss_987654321", name="Customer", short_description="A person or organization that purchases goods or services", long_description="In business, a customer is an individual or organization that purchases goods or services from a company. Customers are vital to the success of any business as they provide revenue and feedback.", status="ENABLED", term_relations={"classifies": ["term_123", "term_456"], "isA": ["term_789"]}, )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
statusNoENABLED
client_tokenNo
term_relationsNo
long_descriptionNo
domain_identifierYes
short_descriptionNo
glossary_identifierYes
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses creation nature, idempotency via client_token, default status, and patterns. Adds behavioral context beyond schema.

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?

Well-structured with Args, Returns, and Example. Slightly verbose but justifies its length by covering all parameters thoroughly. Conciseness is reasonable given schema lack.

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

Completeness4/5

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

Covers all 8 parameters with details, includes return type and example. Lacks prerequisites (e.g., domain and glossary must exist) but good overall for a creation tool without output schema.

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

Parameters5/5

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

Schema coverage is 0%, so description fully compensates. Provides patterns, length constraints, defaults, and an illustrative example for term_relations. Adds significant meaning beyond the schema fields.

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?

Clearly states it creates a business glossary term in Amazon DataZone. Distinguishes from sibling tools like create_glossary (creates glossary) and get_glossary_term (retrieves term).

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?

Implicitly clear that it is for creating terms within an existing glossary, but does not explicitly state when to use vs alternatives like create_glossary or the retrieval tool. No exclusion guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/awslabs/amazon-datazone-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server