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 executes a defined workflow that fetches and processes multiple external URLs, performing indexing operations. While the action is bounded (processing a queue of pre-approved URLs rather than arbitrary code execution), it still constitutes execution of external operations with side effects (indexing, state changes). It is not Read-only since it modifies system state through indexing.
From the tool's definition Tool description states 'Process and index all URLs' and 'Long-running operations will process until the queue is empty', indicating execution of external operations (URL fetching, processing, indexing).
Attacks that exploit this kind of access
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 (jumasheff/mcp-ragdoc-fork). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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