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 Ragdocs. 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.
run_queue triggers real processes with real consequences. An agent gone sideways doesn't fire it once — it starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.
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 Ragdocs, 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.
Free to start. No card required.
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 Ragdocs MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ragdocs 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 Ragdocs. 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 Ragdocs MCP server (sanderkooger/mcp-server-ragdocs). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 7 Ragdocs tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
7 Ragdocs tools catalogued and risk-classified — across an index of 42,500+ MCP servers.