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Canvas LMS MCP Server

by bruchris
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TypeScript
Hybrid

Get Outcome Mastery Distribution

get_outcome_mastery_distribution
Read-only

Retrieve outcome mastery distribution analytics for a Canvas course, with optional filters for specific students, outcomes, and alignment details.

Instructions

Get mastery distribution analytics for outcomes in a course, optionally filtered by students or outcomes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
excludeNoOptional exclusions for missing users or missing outcome results.
course_idYesThe Canvas course ID.
outcome_idsNoOptional outcome IDs to restrict the distribution results.
student_idsNoOptional Canvas student IDs or SIS user IDs prefixed with "sis_user_id:".
add_defaultsNoInclude default mastery colors and levels when Canvas supports it.
only_assignment_alignmentsNoWhen including alignment distributions, limit them to assignments only.
show_unpublished_assignmentsNoInclude unpublished assignments in alignment distributions.
include_alignment_distributionsNoInclude contributing score distributions for alignments.

Schema Changelog

Changes observed during successful MCP inspections.

  1. 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"
  2. Changed2 schema fields changedv1.18.8
    • removedInput schema / properties / student_ids / items / anyOf
      Removed value: -[
-  {
-    "type": "number"
-  },
-  {
-    "type": "string"
-  }
-]
    • addedInput schema / properties / student_ids / items / type
      Added value: +[
+  "number",
+  "string"
+]
  3. First observedv1.18.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows this is a safe, read-only operation. The description adds that it returns analytics and supports filtering, but does not disclose response shape, error conditions, or what the alignment-distribution fields mean. With annotations carrying the safety profile, the description is adequate but not rich.

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?

One sentence packs the verb, resource, scope, and two filtering dimensions with no filler. The core action is front-loaded, making it easy to scan in a long tool list.

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 an 8-parameter analytics tool, the description is sparse but the schema covers each parameter in detail and the annotations handle the safety model. The missing piece is a short sentence on what 'mastery distribution' represents and when the various exclusion/alignment options matter, but an agent can still extrapolate from the parameter descriptions.

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 description coverage is 100%, so all parameters are already documented individually. The description adds only a high-level grouping of filtering by 'students or outcomes', which maps to student_ids/outcome_ids but adds little beyond the schema. Baseline 3 applies here because the schema does the heavy lifting.

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?

The description clearly names the resource ('mastery distribution analytics', 'outcomes in a course') and a specific verb ('Get'), so an agent knows what the tool produces even before opening the schema. It is distinct in concept from sibling tools like get_outcome_results or get_outcome_rollups because it focuses on mastery distribution, but it does not explicitly name those siblings or explain how it differs, so it falls short of full differentiation.

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 choose this tool over the many outcome- or analytics-related siblings. The phrase 'optionally filtered by students or outcomes' tells the reader filters exist but gives no context, expected use case, or mention of alternatives such as get_outcome_contributing_scores or get_course_analytics.

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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