Retrieve current status, execution phase, stable phase-entry timing, latest provider/platform update timing, scheduling delay, routing, failure, and artifact contract details for a specific Jungle Grid job. phase_started_at is when the job first entered the current normalized phase; phase_last_up...
AI agents call get_job to retrieve information from Jungle Grid without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
get_job retrieves operational metadata about an already-submitted GPU workload. It queries existing job state without side effects, making it a Read operation with low severity even though it accesses infrastructure details.
From the tool's definition Tool description uses 'Retrieve' and lists only read-only information retrieval operations: 'current status, execution phase, stable phase-entry timing, latest provider/platform update timing, scheduling delay, routing, failure, and artifact contract details'.
Attacks that exploit this kind of access
Retrieve current status, execution phase, stable phase-entry timing, latest provider/platform update timing, scheduling delay, routing, failure, and artifact contract details for a specific Jungle Grid job. phase_started_at is when the job first entered the current normalized phase; phase_last_updated_at is later provider/platform progress or heartbeat when present; delayed_start identifies a prolonged wait in the actual current phase. A supported estimate does not guarantee immediate or successful runtime startup. It is categorised as a Read tool in the Jungle Grid MCP Server, which means it retrieves data without modifying state.
Register the Jungle Grid MCP server in PolicyLayer and add a rule for 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 Jungle Grid. Nothing to install.
get_job 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 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. 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 is provided by the Jungle Grid MCP server (jungle-grid/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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