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D2L Brightspace MCP Server

D2L Brightspace MCP Server

by bencered
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_course_content

Retrieve course syllabus, modules, topics, lectures, and learning materials to understand course structure and available content.

Instructions

Get the complete course syllabus/structure including all modules, topics, lectures, and learning materials. Returns module titles, descriptions, topic names with URLs, and linked assignments. Use to answer: "What's in this course?", "Show me the syllabus", "What topics are covered?", "What lectures are available?", "What reading materials do I have?"

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_course_content"
  }
}

Input Schema

NameRequiredDescriptionDefault
orgUnitIdNoThe course ID. Optional if D2L_COURSE_ID env var is set.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior3/5

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 describes the return format ('module titles, descriptions, topic names with URLs, and linked assignments'), which is helpful. However, it lacks details on permissions, rate limits, or error handling, leaving behavioral gaps for a read operation.

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 well-structured and front-loaded with the core purpose, followed by return details and usage examples. Every sentence adds value without redundancy, making it efficient and easy to parse.

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?

Given the tool's complexity (retrieving structured course data) and lack of annotations or output schema, the description does a good job covering purpose, usage, and return format. However, it could improve by addressing potential limitations or dependencies (e.g., course availability).

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?

Schema description coverage is 100%, so the baseline is 3. The description adds value by implicitly clarifying the parameter's role in retrieving course content, though it doesn't explicitly mention the orgUnitId parameter. This elevates the score slightly above the baseline.

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 purpose with specific verbs ('Get the complete course syllabus/structure') and resources ('modules, topics, lectures, and learning materials'). It distinguishes from siblings like get_course_module (single module) and get_course_modules (list of modules) by emphasizing comprehensive content retrieval.

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

Usage Guidelines5/5

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

The description explicitly provides usage guidelines by listing example queries ('What's in this course?', 'Show me the syllabus', etc.) that indicate when to use this tool. It implicitly distinguishes from alternatives like get_assignments (specific assignments) or get_announcements (announcements only) by focusing on overall course structure.

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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