AI agents use update_want_to_do to create or update resources in Lapras — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Lapras environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
want_to_do | string | Yes | Career aspirations（今後のキャリアでやりたいこと） |
Parameters from the server's own tool schema.
This tool creates or modifies data reversibly by updating a user's career aspirations on their LAPRAS profile. It does not delete data (ruling out Destructive), does not execute code or trigger external operations (ruling out Execute), involves no financial transactions (ruling out Financial), and is not merely a read operation (ruling out Read).
From the tool's definition Tool description states 'Update career aspirations' and 'on LAPRAS', indicating it modifies user profile data. The name 'update_want_to_do' and description 'Update career aspirations' confirm reversible modification of existing profile information.
Attacks that exploit this kind of access
Update career aspirations（今後のキャリアでやりたいこと） on LAPRAS(https://lapras.com). You can check the result at https://lapras.com/cv. It is categorised as a Write tool in the Lapras MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
update_want_to_do accepts 1 parameter: want_to_do. Required: want_to_do. The full parameter table on this page comes from the server's own tool schema.
Register the Lapras MCP server in PolicyLayer and add a rule for update_want_to_do: 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 Lapras. Nothing to install.
update_want_to_do 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 update_want_to_do 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 update_want_to_do. 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.
update_want_to_do is provided by the Lapras MCP server (@lapras-inc/lapras-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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