tool_get_assignment_details

THE RISK

Low Risk

Why tool_get_assignment_details needs a policy

This tool retrieves and queries assignment metadata without creating, modifying, deleting, or executing any operations. It is a straightforward read operation that poses minimal risk if misused by an AI agent, as it only exposes existing information about an assignment.

From the tool's definition Tool name 'tool_get_assignment_details' and description 'Get detailed information about a specific assignment' indicate a retrieval operation with no modification or side effects.

Documented attack patterns abuse exactly the kind of access tool_get_assignment_details gives an agent:

POLICY

How to control tool_get_assignment_details

PolicyLayer is an MCP gateway — it sits between your AI agents and Gradescope MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for tool_get_assignment_details:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "tool_get_assignment_details": {}
  }
}

tool_get_assignment_details is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

Create a free account and register Gradescope MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

CAP THIS TOOL →

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EXPLORE

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about tool_get_assignment_details

What does the tool_get_assignment_details tool do? +

Get detailed information about a specific assignment. It is categorised as a Read tool in the Gradescope MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on tool_get_assignment_details? +

Register the Gradescope MCP Server MCP server in PolicyLayer and add a rule for tool_get_assignment_details: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Gradescope MCP Server. Nothing to install.

What risk level is tool_get_assignment_details? +

tool_get_assignment_details is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit tool_get_assignment_details? +

Yes. Add a rate_limit block to the tool_get_assignment_details rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block tool_get_assignment_details completely? +

Set action: deny in the PolicyLayer policy for tool_get_assignment_details. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides tool_get_assignment_details? +

tool_get_assignment_details is provided by the Gradescope MCP Server MCP server (yuanpeng-li/gradescope-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Gradescope MCP Server tool call.

Start from Gradescope MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →