High Risk →

restart_model_loading

Restart the PDF models(used by get_stored_response_with_markdown) loading process if it failed or got stuck

How to control restart_model_loading ↓

AI agents invoke restart_model_loading to trigger actions in MCP-RQuest. 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.

High Risk

This tool invokes a restart/recovery operation on a subsystem ('PDF models loading process'), which is an Execute-category action rather than Read, Write, or Destructive. It doesn't retrieve data (Read), modify persistent state reversibly (Write), or delete anything (Destructive), but it does trigger a procedural operation with side effects on the server's internal state.

From the tool's definition Tool performs 'restart' operation on 'PDF models loading process' — a procedural action that triggers an external system state change.

Documented attack patterns abuse exactly the kind of access restart_model_loading gives an agent:

PolicyLayer is an MCP gateway — it sits between your AI agents and MCP-RQuest, and nothing reaches the server without passing your rules. This is the rule we recommend for restart_model_loading:

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "restart_model_loading": {
      "limits": [
        {
          "counter": "restart_model_loading_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

restart_model_loading 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.

  1. Create a free account and register MCP-RQuest — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
RATE-LIMIT THIS TOOL →

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Go deeper

What does the restart_model_loading tool do? +

Restart the PDF models(used by get_stored_response_with_markdown) loading process if it failed or got stuck. It is categorised as a Execute tool in the MCP-RQuest MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on restart_model_loading? +

Register the MCP-RQuest MCP server in PolicyLayer and add a rule for restart_model_loading: 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 MCP-RQuest. Nothing to install.

What risk level is restart_model_loading? +

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

Can I rate-limit restart_model_loading? +

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

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

restart_model_loading is provided by the MCP-RQuest MCP server (xxxbrian/mcp-rquest). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every MCP-RQuest tool call.

Deterministic rules across all 12 MCP-RQuest tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

12 MCP-RQuest tools catalogued and risk-classified — across an index of 42,500+ MCP servers.

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