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Canvas LMS MCP Server

by bruchris
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TypeScript
Hybrid

Create Grading Standard

create_grading_standard
Destructive

Create a letter-to-percentage grading standard in a Canvas course or account. Provide a title and grade thresholds (e.g., A ≥ 94%) to get a reusable standard ID for later course activation.

Instructions

Create a new grading standard (letter-to-percentage scheme) in a course or account context. Provide either course_id or account_id (account requires admin). scheme_entries is an array of { name, value } objects where value is the lower-bound percentage as a fraction 0–1 (e.g. { name: "A", value: 0.94 } means A ≥ 94%). Entries will be sorted descending by value before sending to Canvas. Canvas POST body key is grading_scheme_entry (singular); the returned object uses grading_scheme (plural). Returns the created grading standard object including its id — use that id with apply_grading_standard_to_course to activate it on a course.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesDisplay name for this grading standard (e.g. "GPA 4.0 Scale")
course_idNoCourse ID to create the standard in (mutually exclusive with account_id)
account_idNoAccount ID to create the standard in (requires admin; mutually exclusive with course_id)
scheme_entriesYesGrading scheme entries. Each entry: { name: string, value: number (0–1) }. The lowest grade should have value 0.0.

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. Addedv1.18.3

TDQS

A4.7/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing that entries are sorted descending before sending, that the Canvas body key is grading_scheme_entry while the response uses grading_scheme, and that the response includes the id needed for activation. It also adds the admin requirement, which is not in the schema. The destructiveHint annotation is present but not contradicted by the description.

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?

Every sentence carries actionable information: definition, context selection, entry format, sorting, API key naming, and next-step activation. It is dense but not bloated, and the most critical usage guidance is front-loaded.

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?

Given an output schema is absent, the description compensates by telling the agent what will be returned and how to use it. All required parameters and their semantics are covered, along with the key behavioral quirks an agent needs to call this tool correctly.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaning beyond the schema by explaining how the value field works as a lower-bound fraction, giving an explicit example, noting sorting behavior, and clarifying the mutual exclusivity of course_id and account_id in effect.

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?

States a clear verb-resource pair: 'Create a new grading standard', and explains the concept as a letter-to-percentage scheme. It also differentiates itself from nearby siblings by noting that the returned id should be used with apply_grading_standard_to_course.

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

Usage Guidelines4/5

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

Provides explicit context: choose either course_id or account_id, with account requiring admin. It also tells the agent the follow-up use of the returned id with apply_grading_standard_to_course. It does not explicitly enumerate when not to use the tool, but the guidance is otherwise clear.

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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