Comprehensive analysis of an assignment: status, requirements, materials count, course progress, and deadline info
AI agents call analyze_assignment to retrieve information from Moodle-MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns data about assignments without side effects. It performs analysis and retrieval operations typical of educational LMS systems, consistent with sibling tools like get_assignment_status and get_assignments. No creation, modification, deletion, execution, or financial operations are indicated.
From the tool's definition Tool provides 'comprehensive analysis' and 'retrieves' information (status, requirements, materials count, course progress, deadline info) without modifying or executing any operations. The description uses only informational/retrieval language.
Documented attack patterns abuse exactly the kind of access analyze_assignment gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Moodle-MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for analyze_assignment:
{
"version": "1",
"default": "deny",
"tools": {
"analyze_assignment": {}
}
} analyze_assignment is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Comprehensive analysis of an assignment: status, requirements, materials count, course progress, and deadline info. It is categorised as a Read tool in the Moodle-MCP MCP Server, which means it retrieves data without modifying state.
Register the Moodle- MCP server in PolicyLayer and add a rule for analyze_assignment: 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 Moodle-MCP. Nothing to install.
analyze_assignment is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the analyze_assignment 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.
Set action: deny in the PolicyLayer policy for analyze_assignment. 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.
analyze_assignment is provided by the Moodle- MCP server (loyaniu/moodle-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Moodle-MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
24 Moodle-MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.