Apify MCP: choose Actors, inspect results and save usable JSON

Connect the intended data tools

Thanks to Apify for sponsoring this video.

The video describes Apify Actors as the tools behind the MCP route. Its marketplace count and free allowance reflect the recording, not a current entitlement.

1. Use the recorded /mcp connection sequence and keep the API token private.
2. Choose an Actor that matches the required data and scope.
3. Inspect its inputs, output shape and charging basis before running a large job.
4. Start with a small sample whose results you can check.

Inspect each example against its source

The walkthrough collects leads, researches Amazon listings, clusters Trustpilot sentiment and adds public LinkedIn company information. Those are different datasets with different completeness limits.

1. For a lead list, inspect the source, contact fields and scoring criteria.
2. For prices, keep dates, products and currencies attached to the records.
3. For reviews, compare the sentiment summary with the original text.
4. For enrichment, distinguish available public company facts from missing or inferred data.

Validate the saved output and budget

Saving JSON is useful only when the records and fields are fit for the next job. A collected list is not authorisation to contact anyone on it.

1. Open the saved file and check required fields, duplicates and missing values.
2. Keep source URLs and collection dates where the next task needs them.
3. Inspect actual Actor usage and estimate the intended larger run.
4. Separate data collection from any outreach or other external action.

The takeaway

The workflow turns source data into inspectable files. It does not guarantee complete web access, accurate sentiment labels or permission for downstream messaging.