Canvas LMS MCP Server

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves data ('Get'), implying a read-only operation, but doesn't address permissions, error handling, rate limits, or what happens if the course ID is invalid. For a tool with no annotation coverage, this leaves significant behavioral gaps.

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

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

The description is well-structured and concise, using clear sections (Args, Returns) and minimal sentences. Each part adds value without redundancy. It could be slightly improved by integrating the sections more fluidly, but overall, it's efficient and front-loaded with the core purpose.

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

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

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is partially complete. It covers the basic purpose and parameters but lacks details on usage context, behavioral traits, and output specifics. Without an output schema, it should ideally explain the 'Course object' return value more, but the parameter semantics help offset this gap.

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

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

The description adds meaningful context for both parameters: 'course_id' is explained as 'Course ID', and 'include' as 'Optional list of additional data to include'. With schema description coverage at 0%, this compensates well by clarifying the purpose of each parameter beyond their types. However, it doesn't specify what data can be included in 'include' or provide examples.

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

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

The description clearly states the tool's purpose: 'Get a single course by ID.' It specifies the verb ('Get') and resource ('course'), and distinguishes it from sibling tools like 'list_courses' by focusing on retrieving a single item. However, it doesn't explicitly differentiate from other 'get_' tools (e.g., 'get_assignment'), which slightly limits its specificity.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_courses' for multiple courses or other 'get_' tools for different resources, nor does it specify prerequisites or contexts for usage. This lack of comparative guidance reduces its effectiveness for an AI agent.

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