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kavingas

Catalog Services MCP Server

by kavingas

get_environment_details

Fetch environment details including websites, store views, and export information from Adobe Commerce Catalog Service by providing environment IDs.

Instructions

Get environment details from Catalog Service via HTTP REST API.

This tool calls the /catalog/v1/environments endpoint to retrieve environment 
information including websites, store views, and export details.

Args:
    environment_ids: List of Adobe Commerce Cloud environment IDs 
                    (e.g., ['7059bb71-341a-4ccb-b543-d7b2948b73e4'])
    timeout: Request timeout in seconds (default: 15.0)
    
Returns:
    Dict containing environment information with keys:
    - status: Success or error status
    - environments: List of environment details
    - count: Number of environments retrieved
    
Example:
    >>> result = get_environment_details(
    ...     environment_ids=['7059bb71-341a-4ccb-b543-d7b2948b73e4']
    ... )
    >>> print(result['count'])
    1
    >>> print(result['environments'][0]['websites'])

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
timeoutNo
environment_idsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Description discloses the HTTP endpoint, return structure (status, environments, count), and example output. However, no annotations exist, and the description lacks details on authentication, rate limits, side effects, or error handling. The read-only nature is implied by 'Get' but not explicit.

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?

Description is well-structured with Args, Returns, and an Example section. It is relatively concise for the information provided, though the example could be shortened. Every sentence adds value.

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

Completeness5/5

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

Given the output schema exists and the siblings cover narrower use cases, the description fully covers input, output, endpoint, and usage example. No gaps remain for an agent to invoke the tool correctly.

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

Parameters4/5

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

With schema description coverage at 0%, the description adds crucial meaning: environment_ids gets a realistic example and explanation; timeout gets default and units. Both parameters are well described beyond the bare schema.

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

Purpose4/5

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

Description clearly states the tool retrieves environment details from Catalog Service, naming the endpoint and specifying content (websites, store views, export details). It distinguishes from more specific siblings like get_environment_store_views, though not explicitly limiting scope.

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?

Usage is implied: call when environment details are needed. However, no explicit guidance on when to use this tool vs. siblings (e.g., get_environment_store_views for store views only) or when not to use it.

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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