apply_database_preset
Give a database activity a preset, as Moodle's "Use this preset" does: its fields are added, a field with the same name and type is kept with what entries have in it, every other field is deleted with its content, and its templates replace the database's. Returns the fields. Can delete entries' c...
This record as markdown: /tools/falkenslab-moodle-mcp/apply-database-preset.md
What apply_database_preset does on Moodle
AI agents use apply_database_preset 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 |
|---|---|---|---|
presetId | string | Yes | As list_database_presets gives it |
databaseId | integer | Yes | The database's id (course module id), as get_course_structure gives it |
Parameters from the server's own tool schema.
Why apply_database_preset is rated Medium
An AI agent can call apply_database_preset 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 apply_database_preset 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 apply_database_preset, this is the rule to start with:
apply_database_preset 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 apply_database_preset call is checked against it from then on.
Questions about apply_database_preset
Give a database activity a preset, as Moodle's "Use this preset" does: its fields are added, a field with the same name and type is kept with what entries have in it, every other field is deleted with its content, and its templates replace the database's. Returns the fields. Can delete entries' content: 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.
apply_database_preset accepts 2 parameters: presetId, databaseId. Required: presetId, databaseId. 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 apply_database_preset: 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.
apply_database_preset 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 apply_database_preset 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 apply_database_preset. 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.
apply_database_preset 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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