Run Apify List Store Actors from Claude Code, route the web research output through Deepline, and write the reviewed result into Notion. The page shows which data points move, how the fields map between systems, the pilot command, guardrails, and provider-doc links.
Apify to Notion is a supported Deepline workflow path for Claude Code. Use it when an agent needs to run Apify, inspect the returned fields, and write the reviewed result into Notion with run history, retries, and explicit failure states.
Best query match
“How do I connect Apify to Notion with Claude Code?”
Source primitive
Apify returns structured fields that Deepline records with provider attribution and row-level status.
Destination primitive
Notion receives only reviewed rows after the pilot command succeeds.
This workflow moves data from Apify into Notion with Claude Code as the orchestration layer. It is strongest when you need a repeatable, inspectable handoff with explicit auth, cost math, and recovery steps.
First callable command
curl -s "https://code.deepline.com/api/v2/cli/install" | bash
deepline auth registerApify Web result → Deepline normalized run output
url, query + url, actor_id, input_url, query, dataset_id
Claude Code sees the web result as structured JSON, then Deepline adds provider name, action slug, run ID, retrieved timestamp, and row-level status.
Deepline normalized run output → Notion Review row
source_key, summary, mapped_fields, review_status, run ID, title, status
Use Notion when the workflow output is a research artifact rather than a structured GTM system write.
Notion database or brief → Scheduled Deepline workflow
review status, dedupe key, rollback tag, next run window
After the two-row pilot is approved, the same mapping becomes a scheduled workflow with run history, retries, and loud failures.
Install the Deepline CLI and register your workspace. This gives Claude Code a tested API surface instead of a browser-only workflow.
curl -s "https://code.deepline.com/api/v2/cli/install" | bash
deepline auth registerConnect Apify in the Deepline dashboard. Deepline stores the credential encrypted, exposes a test endpoint, and makes the action callable from Claude Code. Provider reference: https://deepline.com/docs/providers/apify.
Connect Notion as the destination. Use the provider page and docs to confirm required scopes before writing data. Destination reference: https://deepline.com/docs/providers/notion.
Run the smallest useful pilot first. The row range is end-exclusive, so --rows 0:2 tests exactly two rows before a larger batch. Inspect actor input, scraped record, run status plus provider attribution before writing anywhere.
deepline enrich --input leads.csv --output leads.enriched.csv --with 'result=apify_list_store_actors:{}' --jsonAfter the pilot is correct, ask Claude Code to deploy the exact prompt as a Deepline workflow. The mapping from Apify to Notion is preserved with run history, retries, billing visibility, and a rollback tag.
> Use Apify List Store Actors to enrich the input web result, dedupe by domain and email, write results into Notion, and show me the exact rows that changed before deploying the workflow.For 1,000 leads: Pilot first; Deepline credits depend on the selected action and successful results.
Deepline reports Deepline credits and run history. Provider subscriptions or API entitlements stay in the connected provider account.
Claude Code can read the Apify action, run a pilot, inspect the output, and then write only reviewed rows to Notion.
The workflow links the Deepline provider docs, the GTM Provider Directory profile, and related workflow pages so agents can cite the right source before they call a tool.
Once the pilot works, the prompt can run on a schedule with Deepline run history, retry behavior, and explicit failure states.
Cause: The input filter is too narrow, credentials are missing a required scope, or the provider account tier does not expose the action.
Fix: Open the Apify integration in Deepline, run the test endpoint, and then retry the workflow on --rows 0:2 with a broader filter.
Cause: The destination field names, object IDs, campaign IDs, or permissions do not match the connected workspace.
Fix: Use the Notion provider page to inspect the object schema, then map columns explicitly before running the full batch.
Cause: A required ID, campaign name, or date window was hardcoded in the prompt instead of resolved during each run.
Fix: Move IDs into workflow inputs or a lookup step, and keep the scheduled prompt focused on the durable business rule.
Yes. Deepline exposes the Apify action as an agent-callable API/CLI step, so Claude Code can run a pilot, inspect the JSON, and then deploy the same logic as a workflow.
Run a two-row pilot first, inspect provider attribution and dedupe fields, then allow the workflow to write to the destination. This keeps the assertion intact without using a test hack.
It puts primitives first: source provider, destination, action, pilot command, scope assumptions, troubleshooting, and links to the provider docs and related GTM Stack pages.
Connect the LinkedIn scraper and Lemlist in Deepline, paste a post URL into the chat, and Claude scrapes commenters, runs the email waterfall, generates first lines, and drops everyone into your Lemlist campaign.
Connect Apify and HubSpot in Deepline, tell Claude which actor to run and how to map fields, and it runs the scrape + enrichment + HubSpot upsert in one chat.
Connect Apify + HubSpot in Deepline, give Claude a Sales Nav search URL, and it scrapes profiles + runs email waterfall + upserts HubSpot Contacts with persona attributes intact.
Connect Apify + Instantly in Deepline, give Claude a Sales Nav URL, and it scrapes + resolves emails + drops into Instantly with persona vars ready for your templates.
Connect Apify and Instantly in Deepline, pick the actor, and Claude runs scrape + email waterfall + Instantly import.
Run it on Deepline or fork the full skill pack on GitHub. Either way, the code is yours to read and change.