AI agents invoke pull_task to trigger actions in Hive. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
In a broker-worker architecture, 'pull_task' most likely retrieves a pending task from the queue for execution by a worker. This sits between Read (fetching task metadata) and Execute (triggering task execution on a worker). Given the compute cluster context where tasks involve CPU-intensive operations, pulling a task likely initiates or claims it for execution.
From the tool's definition Tool name 'pull_task' in context of a broker-worker compute cluster architecture; description is empty and uninformative.
Documented attack patterns abuse exactly the kind of access pull_task gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Hive, and nothing reaches the server without passing your rules. This is the rule we recommend for pull_task:
{
"version": "1",
"default": "deny",
"tools": {
"pull_task": {
"limits": [
{
"counter": "pull_task_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}pull_task stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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pull_task. It is categorised as a Execute tool in the Hive MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Hive MCP server in PolicyLayer and add a rule for pull_task: 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 Hive. Nothing to install.
pull_task is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the pull_task 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 pull_task. 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.
pull_task is provided by the Hive MCP server (saikodi/hive-compute-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Hive, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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12 Hive tools catalogued and risk-classified — across an index of 43,000+ MCP servers.