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litmos-mcp

litmos-mcp

by dbuxton
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

litmos_list_courses

Read-onlyIdempotent

Retrieve a paginated list of courses from Litmos, including course IDs, names, and codes. Use the IDs to fetch detailed results for a specific user and course combination.

Instructions

List courses available in the Litmos organisation.

Use the returned course IDs with litmos_get_user_course_results to fetch detailed results for a specific user/course combination.

Args: params: CourseListInput with: - limit (int): Records to return, default 100, max 1000 - start (int): Offset for pagination, default 0

Returns: str: JSON array of courses: [{"Id": str, "Name": str, "Code": str, "Active": bool, ...}, ...]

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": {
      "params": "<params>"
    },
    "name": "litmos_list_courses"
  }
}

Input Schema

NameRequiredDescriptionDefault
paramsYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the agent knows the tool is safe and idempotent. The description adds behavioral context about pagination (limit, start parameters) and the return format (JSON array with sample fields), which is valuable beyond the annotations.

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 concise with a clear structure: a lead sentence, a usage hint, an Args section with parameter details, and a Returns section with sample output. Every sentence adds value without redundancy.

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?

The description fully covers the tool's behavior: what it does, its parameters, and the return format (including sample fields). Though there is no explicit output schema, the provided sample structure plus annotations make the tool's behavior complete for this simple paginated list function.

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?

The input schema provides only type and constraints, with 0% description coverage. The description explains both parameters with their purpose, defaults, and bounds (e.g., 'limit (int): Records to return, default 100, max 1000'), which compensates well for the schema's lack of documentation.

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 the tool's function: 'List courses available in the Litmos organisation.' This explicitly identifies the verb (list) and resource (courses), differentiating it from sibling tools like litmos_list_users and litmos_get_user_courses.

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

Usage Guidelines4/5

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

The description provides a concrete usage example: 'Use the returned course IDs with litmos_get_user_course_results to fetch detailed results for a specific user/course combination.' This guides the agent on how to chain tools, though it does not explicitly exclude other usage patterns or compare to siblings.

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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