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Canvas LMS MCP – Remote Edition

by Fireiscoolsolo
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

List Pages

list_pages
Read-onlyIdempotent

List wiki pages in a Canvas course with titles, URL slugs, and last-updated dates to find and read specific pages.

Instructions

List the wiki pages in a course with titles, URL slugs and last-updated dates. Read-only. Read one page with get_page_content using its url slug.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of items to return. Smaller is faster.
course_idYesCanvas course ID, a numeric string such as "12345". Get it from list_courses.
search_termNoOptional text filter on names or titles (at least 2 characters, case-insensitive).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.1.3
    • changedInput schema / properties / course_id / description
      Previous value: -"Canvas course ID"New value: +"Canvas course ID, a numeric string such as \"12345\". Get it from list_courses."
    • changedInput schema / properties / limit / description
      Previous value: -"Max items to return"New value: +"Maximum number of items to return. Smaller is faster."
    • addedInput schema / properties / search_term / description
      Added value: +"Optional text filter on names or titles (at least 2 characters, case-insensitive)."
  2. First observedv0.1.0

TDQS

A4.3/5.0
Behavior3/5

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

The annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint, so safety behavior is covered. The description adds the returned fields and repeats 'Read-only', but does not add further behavioral context such as pagination or rate-limit behavior.

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?

Two short sentences with no wasted text. The core list operation and scope are front-loaded, followed by the minimal alternative pointer.

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

Completeness5/5

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

For a low-complexity list tool with full schema coverage and rich annotations, this is complete enough. It summarizes return fields in place of an output schema and points to the correct sibling for single-page reads.

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 three parameters are already documented by the schema. The description mentions the course scope but adds no syntax or format details beyond the schema, which is the expected baseline when the schema does the heavy lifting.

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 gives a specific verb and resource ('List the wiki pages in a course') and adds the returned fields. It also implicitly distinguishes itself from get_page_content by reserving single-page reading for that sibling.

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?

It explicitly routes single-page reading to get_page_content and names the key to use ('using its url slug'). The when-to-use-this-versus-alternative relationship is clear without needing to infer it.

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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