trigger_crawl
Fires a server-side browser-agent crawl to populate the project's knowledge graph. Localhost URLs tunnel automatically. Returns {executionId, status, targetUrl, durationMs, outcome?, crawlSummary?, knowledgeGraph?, browserSession?} with knowledgeGraph.imported === true on successful ingestion. The b
How to use it
Project documentation lists trigger_crawl for the Debugg Ai MCP MCP server. Add the server to your MCP client (Claude Desktop, Cursor, Windsurf and others), then check which tools your installed version makes available. Tool availability can depend on configuration and credentials. A server handshake does not verify this tool’s behavior. See the full listing for setup details.
Install Debugg Ai MCP
docker run -i --rm --init -e DEBUGGAI_API_KEY=your_api_key quinnosha/debugg-ai-mcpOther tools in Debugg Ai MCP (12)
/ auth.password — pins the precondition login when you also use auth.precondition: "login".
Runs an AI browser agent against your app. The agent navigates, interacts, and reports back with screenshots. Localhost URLs are auto-tunneled via ngrok.
project {action:"create"}
tool, action: "clearSessions" — invalidate the stored sessions so subsequent runs log in. Narrow with username / credentialId; unscoped clears require confirmation because every account on the environment then re-authenticates.
Lightweight no-LLM batch page probe. Pass 1-20 URLs; each navigates, settles on content (the DOM going quiet, bounded — never on network silence, which a live app never reaches), and returns rendered state — screenshot + page metadata + structured console errors + network summary. No agent loop, no
environment {action:"get"} / {action:"list"}
executions {action:"get"\
project {action:"get"} / project {action:"list"}