| name | sales-lobstr |
| description | Lobstr.io platform help — no-code web scraping platform with 50+ ready-made scrapers for Google Maps, LinkedIn Sales Navigator, Twitter, YouTube, and more. Features cookie-based login sync, scheduled automation, multi-threading, and a full API with Python SDK and MCP Server. Use when Lobstr scraper returning empty or incomplete results, exports to Google Sheets or S3 failing, scheduled scrapes not running, API or Python SDK throwing errors, or credits draining faster than expected. Do NOT use for general prospect list strategy (use /sales-prospect-list), cross-platform enrichment strategy (use /sales-enrich), or integration strategy (use /sales-integration). |
| argument-hint | [describe what you need help with in Lobstr.io] |
| license | MIT |
| version | 1.0.0 |
| tags | ["sales","scraping","data-extraction","linkedin","platform"] |
| github | https://github.com/lobstrio |
Lobstr.io Platform Help
Help the user with Lobstr.io platform questions — from configuring ready-made scrapers and running data collection jobs through scheduling automation, exporting results, managing credits, and API integration. Lobstr.io is a no-code web scraping and data collection platform based in Saint-Mandé, France. It offers 50+ ready-made scrapers, multi-threading, cookie-based account sync, scheduled automation, and a full API with Python SDK, CLI, and MCP Server.
Step 1 — Gather context
If references/learnings.md exists, read it first for accumulated knowledge.
Ask the user:
-
What area of Lobstr.io do you need help with?
- A) Ready-made scrapers — choosing and configuring a pre-built scraper (Google Maps, LinkedIn, Twitter, YouTube, etc.)
- B) No-code web app — running scrapers, managing runs, viewing results in the UI
- C) Cookie-based account sync — scraping behind login walls (LinkedIn, etc.) using the cookie picking add-on
- D) Scheduled automation — setting up recurring scraping jobs with triggers
- E) Data export — exporting results to Google Sheets, Amazon S3, or SFTP
- F) Webhooks — configuring run status notifications (run.running, run.paused, run.done, run.error)
- G) API / SDK / CLI — programmatic access, Python SDK, CLI, MCP Server
- H) Make integration — connecting Lobstr to make.com automation workflows
- I) Enterprise custom scrapers — tailored data collectors for specific use cases
- J) Account / Billing / Credits — pricing tiers, credit usage, browsing limits
- K) Safety management — browsing limit protection to avoid account bans
- L) Something else — describe it
-
What's your role?
- A) Sales / business development
- B) Marketing / growth
- C) Developer / engineer
- D) Data analyst / researcher
- E) Agency / freelancer
- F) Other
-
What are you trying to accomplish? (describe your specific goal or question)
If the user's request already provides most of this context, skip directly to the relevant step. Lead with your best-effort answer using reasonable assumptions (stated explicitly), then ask only the most critical 1-2 clarifying questions at the end — don't gate your response behind gathering complete context.
Note: If the user needs a specialized skill, route them there with a brief explanation of why that skill is a better fit.
Step 2 — Route or answer directly
If the request maps to a specialized skill, route: