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Canvas LMS MCP Server

by bruchris
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TypeScript
Hybrid

List Rubrics

list_rubrics
Read-only

List all rubrics in a course.

Instructions

List all rubrics in a course.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
course_idYesThe Canvas course ID

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.18.15
    • addedInput schema / properties / course_id / anyOf
      Added value: +[
+  {
+    "exclusiveMinimum": 0,
+    "maximum": 9007199254740991,
+    "type": "integer"
+  },
+  {
+    "pattern": "^[1-9][0-9]{0,18}$",
+    "type": "string"
+  }
+]
    • removedInput schema / properties / course_id / type
      Removed value: -"number"
  2. Changed1 schema field changedv1.18.11
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  3. First observedv1.18.0

TDQS

B3.2/5.0
Behavior2/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds nothing beyond that – no pagination behavior, result ordering, or whether deleted rubrics are included. With no additional behavioral context supplied, it does not earn credit above the annotation baseline.

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?

A single front-loaded sentence with zero filler, stating subject and scope immediately. Nothing extraneous and nothing buried.

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?

For a single-parameter read-only list tool with complete schema coverage and no output schema, the definition covers what is needed to invoke it correctly. Minor gaps remain around pagination and result shape, but the calling contract is essentially complete.

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%, and course_id is fully documented in the schema ('The Canvas course ID'). The description only implies course scoping and adds no format or semantic detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb ('List') and resource ('rubrics') scoped to a course, so the operation is unambiguous. However, it offers no differentiation from close siblings like get_rubric, create_rubric, or the analogous list_grading_standards, which an agent must disambiguate on its own.

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?

The description gives no when-to-use context, no prerequisites, and no mention of the sibling alternative (get_rubric for a single rubric, list_grading_standards for grading standards). The agent must infer that 'list all' is a bulk read meant for enumeration.

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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