save_submission
Save the logged-in student's submission to an assignment: its online text (HTML, replacing what was there) and files to add (absolute local paths). Doesn't submit it for grading when the assignment asks students to click submit: submit_assignment does. Returns the assignment as the student sees i...
This record as markdown: /tools/falkenslab-moodle-mcp/save-submission.md
What save_submission does on Moodle
AI agents use save_submission 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 |
|---|---|---|---|
files | array | — | |
onlineText | string | — | |
assignmentId | integer | Yes | The assignment's id (course module id), as get_course_structure gives it |
Parameters from the server's own tool schema.
Why save_submission is rated Medium
An AI agent can call save_submission 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.
Attacks that exploit this kind of access
The rule that runs save_submission 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 save_submission, this is the rule to start with:
save_submission 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 save_submission call is checked against it from then on.
Questions about save_submission
Save the logged-in student's submission to an assignment: its online text (HTML, replacing what was there) and files to add (absolute local paths). Doesn't submit it for grading when the assignment asks students to click submit: submit_assignment does. Returns the assignment as the student sees it. Changes the submission: confirm with the person first. 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.
save_submission accepts 3 parameters: files, onlineText, assignmentId. Required: assignmentId. 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 save_submission: 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.
save_submission 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 save_submission 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 save_submission. 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.
save_submission 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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