Low Risk

greenhouse_get_job

Get complete job details by ID. Returns description, requirements, hiring team, and linked applications.

Part of the Greenhouse server.

greenhouse_get_job is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call greenhouse_get_job to retrieve information from Greenhouse without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though greenhouse_get_job only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "greenhouse_get_job": {}
  }
}

See the full Greenhouse policy for all 25 tools.

Get this rule live on your own Greenhouse server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access greenhouse_get_job gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so greenhouse_get_job only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the greenhouse_get_job tool do? +

Get complete job details by ID. Returns description, requirements, hiring team, and linked applications.. It is categorised as a Read tool in the Greenhouse MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on greenhouse_get_job? +

Register the Greenhouse MCP server in PolicyLayer and add a rule for greenhouse_get_job: 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 Greenhouse. Nothing to install.

What risk level is greenhouse_get_job? +

greenhouse_get_job is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit greenhouse_get_job? +

Yes. Add a rate_limit block to the greenhouse_get_job 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.

How do I block greenhouse_get_job completely? +

Set action: deny in the PolicyLayer policy for greenhouse_get_job. 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.

What MCP server provides greenhouse_get_job? +

greenhouse_get_job is provided by the Greenhouse MCP server (https://gateway.pipeworx.io/greenhouse/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Greenhouse tool call.

Deterministic rules across all 25 Greenhouse tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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