export_grades
Save a course's grades into a local folder as Moodle exports them for a teacher: a spreadsheet (xlsx, ods), CSV or XML, with the items, group, display and feedback chosen. The file names every participant: only with names in clear (the server's student data level), since a file can't be pseudonym...
This record as markdown: /tools/falkenslab-moodle-mcp/export-grades.md
What export_grades does on Moodle
AI agents use export_grades to create or update resources in Moodle, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Moodle environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
format | string | Yes | |
destDir | string | Yes | An absolute local folder |
display | array | — | |
groupId | integer | — | |
itemIds | array | — | Only these grade items |
courseId | integer | Yes | |
feedback | boolean | — | Include feedback |
Parameters from the server's own tool schema.
Why export_grades is rated Medium
An AI agent can call export_grades faster than any human can review: one bad instruction and it creates or modifies resources in Moodle by the hundred, each call as confident as the last.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs export_grades safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Moodle, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For export_grades, this is the rule to start with:
export_grades stays usable, but capped: an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Moodle, apply this rule, and every export_grades call is checked against it from then on.
Questions about export_grades
Save a course's grades into a local folder as Moodle exports them for a teacher: a spreadsheet (xlsx, ods), CSV or XML, with the items, group, display and feedback chosen. The file names every participant: only with names in clear (the server's student data level), since a file can't be pseudonymized. It is categorised as a Write tool in the Moodle MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
export_grades accepts 7 parameters: format, destDir, display, groupId, itemIds, courseId, feedback. Required: format, destDir, courseId. The full parameter table on this page comes from the server's own tool schema.
Register the Moodle MCP server in PolicyLayer and add a rule for export_grades: 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. Nothing to install.
export_grades is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the export_grades 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 export_grades. 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.
export_grades is provided by the Moodle MCP server (@falkenslab/moodle-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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