Canvas MCP has 6 tools with consistently present descriptions and parameter schemas. All tools use clear action verbs (get_, list_) and are READ_ONLY. Descriptions are adequate but vary in specificity. Parameter schemas are well-typed with descriptions. However, output schemas are undocumented, error handling guidance is minimal, and some parameter descriptions lack format constraints. Tool composition is reasonable, each tool has a single responsibility. No security issues detected in parameter definitions (no secrets exposed). The server uses FastMCP on HTTP/STDIO transports.

• Add explicit output schemas to all tools. Document return types in the server initialization or add a 'Returns' section to each tool description. Example: 'Returns a list of objects with fields: id (int), name (str), members (list[dict]).'
• Convert 'sort_by' parameter values to an enum constraint rather than listing them in the description. This allows LLMs to select from validated options without hallucinating.
• Add min/max bounds to numeric parameters. E.g., 'days: integer, range 1-365 (default: 7)'.
• Document pagination for list_* tools. Add optional 'limit' and 'offset' or 'cursor' parameters; clarify max result size and provide cursor for next page.
• Add error handling guidance to tool descriptions. Example: 'If the course is not found, the LLM should try searching for the course by name first using a hypothetical search_courses tool or prompt the user to verify the course ID.'
• Clarify the 'course_identifier' parameter type in each tool. Example: 'Course identifier: Canvas course ID (integer, e.g., 12345) or course code (string, e.g., 'CS101'). If using a code, ensure it is unique within your Canvas instance.'
• Document which parameters have defaults. E.g., 'include_participation' defaults to true; clarify what happens if omitted.
• Add a 'Group by' or additional sorting columns to get_student_analytics to enable filtering by engagement score ranges (e.g., 'show only students with engagement < 50').