View job applications across your pipeline. Returns applicant names, job IDs, application status, and submission dates. Filter by job or stage (e.g., 'screening', 'interview').
Part of the Greenhouse server.
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AI agents call greenhouse_list_applications 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_list_applications 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.
{
"version": "1",
"default": "deny",
"tools": {
"greenhouse_list_applications": {}
}
}See the full Greenhouse policy for all 25 tools.
These attack patterns abuse exactly the kind of access greenhouse_list_applications gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
View job applications across your pipeline. Returns applicant names, job IDs, application status, and submission dates. Filter by job or stage (e.g., 'screening', 'interview').. It is categorised as a Read tool in the Greenhouse MCP Server, which means it retrieves data without modifying state.
Register the Greenhouse MCP server in PolicyLayer and add a rule for greenhouse_list_applications: 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.
greenhouse_list_applications 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 greenhouse_list_applications 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 greenhouse_list_applications. 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.
greenhouse_list_applications 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.
Deterministic rules across all 25 Greenhouse tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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