mcp-magento-cloud

list_services

List services in a Magento Cloud project by providing project ID and environment, returning versions and disk allocation for MySQL, Redis, OpenSearch, RabbitMQ, and more.

Instructions

List services (MySQL, Redis, OpenSearch, RabbitMQ, etc.) in a Magento Cloud project with their versions and disk allocation

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "project": "<project>",
      "environment": "<environment>"
    },
    "name": "list_services"
  }
}

Input Schema

Name	Required	Description	Default
`project`	Yes	The Magento Cloud project ID
`environment`	Yes	The environment name, e.g. 'staging', 'production'

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.4.0Jul 29, 2026

TDQS

A3.7/5.0

Behavior3/5

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

With no annotations, the description carries full responsibility. The verb 'List' implies a read-only operation, which is helpful but not explicitly stated. No additional behavioral context (e.g., safety, permissions, rate limits) is provided, making it minimally adequate.

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

Conciseness5/5

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

The description is a single, well-structured sentence that conveys all necessary information without any fluff. Every word adds value, and it is front-loaded with the action and resource.

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?

For a simple list tool with two clearly defined parameters and no output schema, the description fully covers what the tool does and what it returns (service versions and disk allocation). No additional information is needed for an AI agent to use this tool correctly.

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 100% with both parameters having clear descriptions. The tool description adds no extra meaning beyond the schema; it only repeats that the project is a Magento Cloud project, which is already inherent in the tool's context.

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 uses a specific verb ('List'), names the resource ('services in a Magento Cloud project'), and provides concrete examples (MySQL, Redis, OpenSearch, RabbitMQ) and what is included (versions and disk allocation). This clearly defines the tool's purpose and distinguishes it from sibling tools that list other resources (e.g., list_log_types, list_projects).

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives. The description never mentions when to choose list_services over other list tools, nor does it state prerequisites 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.

Deploy Server