hub_parallel_query · Llama Maverick Hub MCP Server MCP

WHAT IT DOES

What hub_parallel_query does on Llama Maverick Hub MCP Server

AI agents invoke hub_parallel_query to trigger actions in Llama Maverick Hub MCP Server. 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.

WHY IT NEEDS A POLICY

Why hub_parallel_query needs a policy

Although named 'query', this tool triggers execution across multiple external services in parallel (including financial services like Stripe and databases). The blast radius is high because a misrouted or malicious call could simultaneously affect multiple services.

From the tool's definition 'Query multiple services in parallel' — the tool executes coordinated operations across multiple MCP services (Stripe, GitHub, databases) simultaneously

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

hub_parallel_query Rate-limited

hub_parallel_query 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "hub_parallel_query": {
      "limits": [
        {
          "counter": "hub_parallel_query_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Llama Maverick Hub MCP Server, so you can run agents against it safely.

FAQ

Questions about hub_parallel_query

What does the hub_parallel_query tool do? +

Query multiple services in parallel and aggregate results. It is categorised as a Execute tool in the Llama Maverick Hub MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on hub_parallel_query? +

Register the Llama Maverick Hub MCP Server MCP server in PolicyLayer and add a rule for hub_parallel_query: 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 Llama Maverick Hub MCP Server. Nothing to install.

What risk level is hub_parallel_query? +

hub_parallel_query is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit hub_parallel_query? +

Yes. Add a rate_limit block to the hub_parallel_query 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 hub_parallel_query completely? +

Set action: deny in the PolicyLayer policy for hub_parallel_query. 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 hub_parallel_query? +

hub_parallel_query is provided by the Llama Maverick Hub MCP Server MCP server (yobieben/llama-maverick-hub-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.