RFC: an MCP server for Crawlee Cloud — let AI agents drive your scrapers #96
aminembarki
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I want Crawlee Cloud instances to be first-class tools for AI agents. The Model Context Protocol is how Claude, Cursor, and a growing list of agent runtimes talk to external systems — and "run this scraper, wait for it, hand me the dataset" is about as natural an agent workflow as it gets.
The proposal: a platform MCP server. One server, built in TypeScript inside the existing monorepo (as a new package or a
crc mcpsubcommand — genuinely undecided, tell me which you'd prefer), targeting the platform exactly as it is today. It would expose tools along the lines of:run-actor— start a run with input, optionally wait for completionget-run-status— check a run's stateget-dataset-items— fetch results as JSONstream-logs— tail a run's logsEverything talks to the same Apify-compatible v2 API the CLI uses, authenticated with your existing API key. Nothing about the platform changes; this is a new front door, not a new engine. It does not depend on the Python support RFC — it works with today's TypeScript actors from day one.
For a possible layer two: Apify's own actors-mcp-server exposes each actor as its own MCP tool, with parameters derived from the actor's input schema — an agent calls
scrape-amazondirectly instead of a genericrun-actor. That's attractive but heavier; I'd rather ship the platform server first and layer this on if people want it.What I need from you:
npx) is simplest; a remote/HTTP endpoint on your instance means any agent can connect without local setup but raises the auth stakes. Which fits your deployment?Ground rules:
This is on the roadmap as Proposed — RFC open: no version commitment until this discussion converges. Would you point an agent at your instance — and what would it need to do?
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