AI agents call get_job_detail to retrieve information from Lapras without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
jobId | string | Yes | The unique identifier of the job posting |
Parameters from the server's own tool schema.
This tool retrieves and queries job posting details without modifying any data or triggering external operations. It is a straightforward read operation with no side effects, matching the Read category definition of 'retrieves or queries data; no side effects (search, list, get, fetch).' The tool does not create, modify, delete, or execute actions; it only fetches information.
From the tool's definition Tool description states 'Get detailed information about a specific job posting' and 'You can apply for jobs through the URL provided in the response.' The primary action is retrieval of job posting data.
Attacks that exploit this kind of access
Get detailed information about a specific job posting. You can apply for jobs through the URL provided in the response. It is categorised as a Read tool in the Lapras MCP Server, which means it retrieves data without modifying state.
get_job_detail accepts 1 parameter: jobId. Required: jobId. 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 get_job_detail: 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.
get_job_detail is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_job_detail 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 get_job_detail. 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.
get_job_detail 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.
get_job_detail is one line of Lapras's registry record.
The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.
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