Process and index all URLs currently in the documentation queue. Each URL is processed sequentially, with proper error handling and retry logic. Progress updates are provided as processing occurs. Use this after adding new URLs to ensure all documentation is indexed and searchable. Long-running o...
AI agents invoke run_queue to trigger actions in RAG Documentation 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.
This tool triggers a computational operation (URL processing, indexing) that executes against external resources and has side effects on the system state (queue processing, index updates). While not destructive or financial, and clearly not a simple read operation, it performs an execute-class action. The 'long-running' nature and mention of error handling with retries indicates complex execution logic.
From the tool's definition Tool description states it will 'Process and index all URLs' with 'Long-running operations' that continue 'until the queue is empty or an unrecoverable error occurs.' The action of processing external URLs and indexing them represents code execution with…
Documented attack patterns abuse exactly the kind of access run_queue gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and RAG Documentation MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for run_queue:
{
"version": "1",
"default": "deny",
"tools": {
"run_queue": {
"limits": [
{
"counter": "run_queue_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}run_queue 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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Process and index all URLs currently in the documentation queue. Each URL is processed sequentially, with proper error handling and retry logic. Progress updates are provided as processing occurs. Use this after adding new URLs to ensure all documentation is indexed and searchable. Long-running operations will process until the queue is empty or an unrecoverable error occurs. It is categorised as a Execute tool in the RAG Documentation MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the RAG Documentation MCP Server MCP server in PolicyLayer and add a rule for run_queue: 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 RAG Documentation MCP Server. Nothing to install.
run_queue 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 run_queue 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 run_queue. 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.
run_queue is provided by the RAG Documentation MCP Server MCP server (rahulretnan/mcp-ragdocs). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 14 RAG Documentation MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
14 RAG Documentation MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.