Gradescope MCP Server

tool_grade_answer_group

Apply consistent rubric items, point adjustments, and comments to all student submissions within a designated answer group simultaneously.

Instructions

Batch-grade ALL submissions in an answer group at once.

**WARNING**: This grades N students at once. Use with caution.

Args:
    course_id: The Gradescope course ID.
    question_id: The question ID.
    group_id: The answer group ID.
    rubric_item_ids: Rubric item IDs to apply.
    point_adjustment: Point adjustment.
    comment: Grader comment.
    confirm_write: Must be True to apply grades.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "course_id": "<course_id>",
      "question_id": "<question_id>",
      "group_id": "<group_id>"
    },
    "name": "tool_grade_answer_group"
  }
}

Input Schema

Name	Required	Description	Default
`course_id`	Yes
`question_id`	Yes
`group_id`	Yes
`rubric_item_ids`	No
`point_adjustment`	No
`comment`	No
`confirm_write`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Mar 18, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it's a batch operation affecting multiple students, includes a safety warning, and specifies a confirm_write parameter as a safeguard. It doesn't detail permissions, rate limits, or exact effects on grades, but covers essential mutation context.

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?

The description is front-loaded with the core purpose and warning, followed by a structured Args section. Every sentence earns its place: the first states the action, the second warns, and the parameter list is necessary given low schema coverage. No wasted words.

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?

Given a complex mutation tool with 7 parameters, 0% schema coverage, no annotations, but an output schema exists, the description is mostly complete. It covers purpose, caution, and parameter meanings, but could benefit from more on prerequisites or error handling. The output schema reduces need for return value details.

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 description coverage is 0%, so the description must compensate. It lists all 7 parameters with brief explanations (e.g., 'Rubric item IDs to apply,' 'Point adjustment,' 'Grader comment'), adding meaningful semantics beyond the schema's titles. However, it lacks details on formats or constraints for IDs and adjustments.

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 clearly states the specific action ('batch-grade ALL submissions'), the target resource ('answer group'), and scope ('at once'). It distinguishes from sibling tools like tool_apply_grade (which likely grades individual submissions) by emphasizing the batch nature and N students scope.

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?

The description provides clear context with the 'WARNING' about grading N students at once and 'Use with caution,' which implicitly guides when to use this tool versus individual grading alternatives. However, it doesn't explicitly name alternative tools or state when-not-to-use scenarios beyond the caution.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server