---
schema: 1
type: video
title: 'From MCP to Scale: Pipelines That Build Themselves — Rafael Levi, Bright Data'
description: >-
  Scraping is not the hard part anymore. Maintaining scrapers is. This session
  shows what it looks like when an agent uses MCP to inspect a site, understand
  its structure, generate a production scraper, and keep that pipeline working
  when the site changes. Using Bright Data's MCP, APIs, and browser
  infrastructure, the flow moves from one-off extraction to something much more
  useful: agents that build parsers, save tokens by switching from page parsing
  to reusable scripts, and repair broken collection jobs without a human getting
  dragged in at 2am. If you're thinking about web data, automation, or agents
  that operate beyond a single prompt, this is a practical look at pipeline
  building at scale. Speaker info: - https://il.linkedin.com/in/rafael-levi -
  https://github.com/ScrapeAlchemist --- Watch along with the corrected
  transcript, summary, timestamps and resources on this talk's official AIE
  page:
  https://ai.engineer/talks/zTZ0qunQXnM-from-mcp-to-scale-pipelines-that-build-themselves
  Join our upcoming AI Engineer conferences (see https://ai.engineer landing
  page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs
  and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference
  returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS
  2026 in Sydney ---
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parent: 'https://liquidgold.cc/channel/aidotengineer.md'
channel: aidotengineer
updated: '2026-10-24T09:46:39.771Z'
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# From MCP to Scale: Pipelines That Build Themselves — Rafael Levi, Bright Data

Scraping is not the hard part anymore. Maintaining scrapers is. This session shows what it looks like when an agent uses MCP to inspect a site, understand its structure, generate a production scraper, and keep that pipeline working when the site changes. Using Bright Data's MCP, APIs, and browser infrastructure, the flow moves from one-off extraction to something much more useful: agents that build parsers, save tokens by switching from page parsing to reusable scripts, and repair broken collection jobs without a human getting dragged in at 2am. If you're thinking about web data, automation, or agents that operate beyond a single prompt, this is a practical look at pipeline building at scale. Speaker info: - https://il.linkedin.com/in/rafael-levi - https://github.com/ScrapeAlchemist --- Watch along with the corrected transcript, summary, timestamps and resources on this talk's official AIE page: https://ai.engineer/talks/zTZ0qunQXnM-from-mcp-to-scale-pipelines-that-build-themselves Join our upcoming AI Engineer conferences (see https://ai.engineer landing page): - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS 2026 in Sydney ---

Canonical: https://liquidgold.cc/watch/zTZ0qunQXnM · Channel: [AI Engineer](https://liquidgold.cc/channel/aidotengineer.md)

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