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List Course Users

list_course_users
Read-only

List users in a course with optional Canvas filters. Use include to request email, enrollments, avatar_url, bio, and other fields otherwise omitted from the default response.

Instructions

List users in a course with optional Canvas filters. Use include to request email, enrollments, avatar_url, bio, and other fields otherwise omitted from the default response. Use enrollment_type / enrollment_state to narrow by role or status, search_term to filter by name/login, user_ids to fetch a specific subset, and sort/order to control ordering.

Input Schema

NameRequiredDescriptionDefault
sortNoSort field
orderNoSort order
includeNoExtra fields to include on each user (Canvas include[] param)
user_idsNoRestrict the result to the given user IDs (pass large IDs as strings). SIS user IDs may be given as "sis_user_id:<sis id>".
course_idYesThe Canvas course ID
search_termNoPartial name or full login/SIS ID to filter users by
enrollment_typeNoFilter by one or more enrollment types
enrollment_stateNoFilter by enrollment state (e.g. active, invited)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 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}$",
      +    "type": "string"
      +  }
      +]
    • removedInput schema / properties / course_id / type
      Removed value: -"number"
    • changedInput schema / properties / user_ids / description
      Previous value: -"Restrict the result to the given user IDs"New value: +"Restrict the result to the given user IDs (pass large IDs as strings). SIS user IDs may be given as \"sis_user_id:<sis id>\"."
    • addedInput schema / properties / user_ids / items / anyOf
      Added value: +[
      +  {
      +    "exclusiveMinimum": 0,
      +    "maximum": 9007199254740991,
      +    "type": "integer"
      +  },
      +  {
      +    "pattern": "^[1-9][0-9]{0,18}$",
      +    "type": "string"
      +  },
      +  {
      +    "pattern": "^sis_user_id:[\\s\\S]+$",
      +    "type": "string"
      +  }
      +]
    • removedInput schema / properties / user_ids / items / type
      Removed value: -[
      -  "number",
      -  "string"
      -]
  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. Changed2 schema fields changedv1.18.8
    • removedInput schema / properties / user_ids / items / anyOf
      Removed value: -[
      -  {
      -    "type": "number"
      -  },
      -  {
      -    "type": "string"
      -  }
      -]
    • addedInput schema / properties / user_ids / items / type
      Added value: +[
      +  "number",
      +  "string"
      +]
  4. First observedv1.18.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered. The description adds real behavioral context by disclosing that the default response omits fields like email, bio, and avatar_url unless requested via include — useful for predicting output shape. It stops short of describing pagination or result limits.

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

Conciseness4/5

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

Two sentences, front-loaded with the core operation before the filter enumeration, and no filler. The long filter clause is dense but each element maps to a real parameter, so nothing is wasted.

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 read-only list endpoint with no output schema, the description covers the operation, the filter surface, and the default-vs-included field behavior, which is enough to call it correctly. The missing pieces — pagination behavior and how it differs from sibling user-listing tools — are minor.

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 the schema already documents all eight parameters and their enums; that sets the baseline at 3. The description restates the roles of enrollment_type/enrollment_state, search_term, user_ids, and sort/order, adding mild interpretive value ('narrow by role or status') but no syntax or format details beyond the schema.

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 names a specific verb+resource+scope ('List users in a course') and enumerates the filterable dimensions, so the operation is unambiguous. It does not, however, distinguish itself from nearby siblings like list_students, search_users, or list_account_users, which could plausibly return overlapping results.

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

Usage Guidelines3/5

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

It explains what each filter does, which implies usage, but never states when to reach for this tool versus search_users or list_students, nor any prerequisites (e.g. enrollment/permission requirements to see course rosters). Usage is inferred rather than directed.

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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