browser_select
Choose options in a select of the browser tools' tab by its snapshot ref, by their values or visible labels (several for a multiple select). A fallback: use it only when no Moodle tool covers the task, and say which task, so a tool can be made for it.
This record as markdown: /tools/falkenslab-moodle-mcp/browser-select.md
What browser_select does on Moodle
AI agents use browser_select 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 |
|---|---|---|---|
ref | string | Yes | The element's ref from the latest browser_snapshot, like e12 |
options | array | Yes |
Parameters from the server's own tool schema.
Why browser_select is rated Medium
An AI agent can call browser_select 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 browser_select 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 browser_select, this is the rule to start with:
browser_select 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 browser_select call is checked against it from then on.
Questions about browser_select
Choose options in a select of the browser tools' tab by its snapshot ref, by their values or visible labels (several for a multiple select). A fallback: use it only when no Moodle tool covers the task, and say which task, so a tool can be made for it. 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.
browser_select accepts 2 parameters: ref, options. Required: ref, options. 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 browser_select: 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.
browser_select 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 browser_select 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 browser_select. 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.
browser_select 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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