Newsletter Sponsor Intelligence

Find newsletter and podcast sponsor evidence, creator contacts, and audience-fit signals.

What this Actor returns

• publicationName
• platform
• publicationUrl
• authorName
• sponsorBrand
• evidenceText
• evidenceUrl
• postDate
• estimatedSubscribers
• topics
• contactEmail
• socialLinks
• sponsorFitScore
• confidenceScore
• scrapedAt
• sourceUrl

How to use it

1. Run once with the default input to validate the output schema.
2. Add public startUrls for live extraction where the target source allows public access.
3. Disable fallbackToSampleIfEmpty when you want failed/empty live runs to stay empty.
4. Schedule the Actor for monitoring workflows and export the dataset to JSON, CSV, Excel, API, or webhooks.

Production notes

This Actor ships with a typed input schema, dataset schema, store icon, defensive parsing, sample data for integration tests, and generic public-page extraction. Some target platforms are dynamic, protected, or login-gated; for those, production-grade coverage should use compliant public URLs, official/export APIs, or a maintained provider adapter.

Input example

{}

All fields are described in the Input tab, and the same JSON works in the API and for AI agents.

Output example

Each result is one dataset item. A real item from a test run (long fields shortened):

{
  "publicationName": "Netflix Earnings, Business or Franchise, Disney’s Deal",
  "platform": "rss",
  "publicationUrl": "https://stratechery.com/feed/",
  "authorName": "Ben Thompson",
  "sponsorBrand": null,
  "evidenceText": "Netflix has a solid business, which is exactly the problem: the company increasingly seems like a business and not a franchise, at least in terms of growth.<...",
  "evidenceUrl": "https://stratechery.com/2026/netflix-earnings-business-or-franchise-disneys-deal/",
  "postDate": "Wed, 21 Oct 2026 10:00:00 +0000",
  "estimatedSubscribers": null,
  "topics": [],
  "contactEmail": null,
  "socialLinks": []
}

How much does Newsletter Sponsor Intelligence cost?

This Actor uses pay-per-event pricing: you pay only for what it delivers, and platform usage is included.

Event	Price
Result (one dataset item)	$0.008 each ($8.00 per 1,000)
Actor start	$5e-05 per run

Set Maximum cost per run in the run options to cap your spend; the Actor stops when the limit is reached. Check the Pricing tab for current prices and plan discounts.

Use Newsletter Sponsor Intelligence with AI agents (MCP)

Give Claude, ChatGPT, Cursor, VS Code or any MCP client this Actor as a tool through the hosted Apify MCP server. The agent sees the input fields with descriptions and example values, runs the Actor, and reads the results.

MCP server URL (this Actor only):

https://mcp.apify.com/?tools=technicaldost/newsletter-sponsor-intelligence

Claude Code:

$claude mcp add --transport http apify "https://mcp.apify.com/?tools=technicaldost/newsletter-sponsor-intelligence" --header "Authorization: Bearer YOUR_APIFY_TOKEN"

Cursor, VS Code, Claude Desktop and other clients (mcp.json or the client's MCP settings):

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=technicaldost/newsletter-sponsor-intelligence",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

Clients that support sign-in (such as Claude.ai connectors) can use the URL without a token and log in to Apify instead. Get your token in Apify Console → Settings → API & Integrations, or generate a ready config for your client at mcp.apify.com. In the agent the tool is named technicaldost--newsletter-sponsor-intelligence; ask it, for example, to "run Newsletter Sponsor Intelligence with {}".

AI agents without an Apify account can also run and pay for this Actor per request with x402 agentic payments.

Run Newsletter Sponsor Intelligence via API

Run the Actor and get its results in one call (replace YOUR_APIFY_TOKEN):

curl -X POST "https://api.apify.com/v2/acts/technicaldost~newsletter-sponsor-intelligence/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{}'

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("technicaldost/newsletter-sponsor-intelligence").call(run_input={})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript / TypeScript (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('technicaldost/newsletter-sponsor-intelligence').call({});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Long runs: start them with POST /v2/acts/technicaldost~newsletter-sponsor-intelligence/runs and fetch the dataset when the run finishes, or receive a webhook.

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FAQ

Can I use Newsletter Sponsor Intelligence with AI agents like Claude or ChatGPT?

Yes. Connect the Apify MCP server with ?tools=technicaldost/newsletter-sponsor-intelligence (see above) and the agent can run the Actor and read its results on its own.

Can I call Newsletter Sponsor Intelligence from my own code?

Yes. Use the REST API, or the official Python and JavaScript clients shown above. Results are available as JSON, CSV, Excel, XML or HTML.

How do I run it on a schedule?

Save your input as a task in Apify Console and add a schedule (for example, daily). Use webhooks or integrations to send each run's results onward.

Is it legal to use this Actor?

It works with publicly available data. Make sure your use complies with the source website's terms and with data protection laws such as GDPR, especially for personal data.

Something doesn't work or I need a feature. What should I do?

Open an issue in the Issues tab on this Actor's page with an example input, and we'll look into it.