Restart the PDF models(used by get_stored_response_with_markdown) loading process if it failed or got stuck
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.
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:
{
"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.
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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.
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.
restart_model_loading 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 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.
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.
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.
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.