Documentation
Extralt goes beyond ecommerce scraping. Extract public product and catalog pages, enrich the resulting Captures into normalized Items, connect records across stores, and inspect the customer dataset through the dashboard, the API and its SDKs, and MCP.
The documentation separates three things that are easy to confuse:
- operations such as Robots, Runs, Schedules, Imports, and Enrichments;
- data such as Captures, Items, Products, Variants, Listings, Offers, Reviews, Stores, and Changes;
- access surfaces such as dashboard views, API resources, the Python and TypeScript SDKs, exports, OAuth-authenticated MCP tools, dashboard AI queries, and the dashboard agent.
Getting started
New to Extralt? Start with the introduction, then follow the guides for account setup, robots, imports, and scheduling.
Introduction
Understand the product, pipeline, and boundaries.
Guides
Run extraction, enrichment, exploration, dashboard Agent, and MCP workflows.
Data
Grains, lineage, query fields, relationships, and interpretation rules.
Using the API
Authentication, the Python and TypeScript SDKs, request conventions, and limits.
Concepts
How Extralt works under the hood.
Reference
Precise definitions for operations and analytical entities.
Key concepts
The platform follows three stages: Extract collects ecommerce page data as Captures, Enrich produces normalized Items and publishes their cross-store relationships, and Explore turns that connected model into evidence views, four Analyses, custom Query results, and Agent answers.