News & RSS Monitor — Google Alerts Alternative

Monitor topics and brands through GDELT and selected public feeds. Export deduplicated headlines, article links, matched queries, publisher details, and fresh-item flags for recurring news-monitoring workflows. For communications teams, each dataset row is one deduplicated article alert with its matched query and freshness context.

Workflow: put the results to work

Define explicit watch queries and the trusted feeds relevant to your coverage. Keep a stable alert ID when using cross-run deduplication, then route newly observed articles into your editorial or research queue. Review source coverage before interpreting a quiet result set.

Best fit and workflow guidance

Choose this Actor when a founder, analyst, communications team, or AI workflow needs structured current-news alerts for an explicit watchlist. It works well for a saved Apify task that runs on a schedule, sends the dataset to a spreadsheet or webhook, and highlights items that have not appeared in earlier runs. Pair it with your own notification or reporting destination when the next step is email delivery, a team chat post, or a dashboard.

Use a dedicated media-intelligence suite when the workflow calls for a licensed media archive, broad social listening, broadcast coverage, PR outreach, or a collaborative enterprise workspace. This Actor focuses on current public-news and selected-feed collection with inspectable source provenance.

Input

Start with one focused query and a daily-sized window. A stable alertId keeps the same deduplication state across scheduled runs.

{
  "alertId": "ai-company-news",
  "watchQueries": ["OpenAI", "Anthropic"],
  "sourceMode": "gdeltOnly",
  "trustedSources": [],
  "lookbackHours": 24,
  "maxItems": 25,
  "excludeKeywords": ["sponsored"],
  "dedupeAcrossRuns": true,
  "includePreviouslySeen": false,
  "resetAlertState": false,
  "stateRetentionDays": 30
}

Choose gdeltAndFeeds to supplement the public-news query with RSS, Atom, or JSON feeds that you select. Feed URLs pass public-network checks, bounded redirect handling, and format validation before parsing. A feed-only mode is also available for a controlled publisher-watch workflow.

GDELT is an upstream public-news service, so temporary rate or network responses can occur. The Actor makes up to six bounded attempts for a transient GDELT response and returns a named diagnostic outcome with full run details. For the most controlled recurring workflow, include the relevant publisher feeds in gdeltAndFeeds or use feedsOnly.

Output dataset

Each row is one normalized article identity after source merging and recurring-alert deduplication. Source-derived fields stay null when a source does not provide them, preserving a clear view of what was collected.

Field	Meaning
title, url, snippet, publishedAt	Article details supplied by an upstream public source
matchedQueries	Configured watch queries that produced or matched the item
publisherName, publisherUrl, language, sourceCountry	Publisher and source metadata when available
sourceTypes, sourceNames, sources	GDELT and selected-feed provenance for the deduplicated item
attributions	Required source attribution records, including GDELT Project attribution
isNew, alertId, collectedAt	Recurring-alert state and collection-time details

{
  "id": "a5b9d359b42cc3d4dcfa3d8a1ea893e9e9398e30c2eb5dd31ea5a77786c27afb",
  "alertId": "ai-company-news",
  "title": "Example article headline",
  "url": "https://example.org/news/example-article",
  "matchedQueries": ["OpenAI"],
  "publisherName": "example.org",
  "publisherUrl": "https://example.org/",
  "sourceTypes": ["gdelt"],
  "sourceNames": ["GDELT Project DOC API"],
  "sourceTags": [],
  "snippet": null,
  "publishedAt": "YYYY-MM-DDTHH:mm:ss.sssZ",
  "language": "English",
  "sourceCountry": "United States",
  "collectedAt": "YYYY-MM-DDTHH:mm:ss.sssZ",
  "isNew": true,
  "sources": [
    {
      "sourceType": "gdelt",
      "sourceName": "GDELT Project DOC API",
      "sourceUrl": "https://api.gdeltproject.org/api/v2/doc/doc?query=OpenAI",
      "feedUrl": null,
      "feedType": null,
      "provider": "GDELT Project",
      "attributionName": "GDELT Project",
      "attributionUrl": "https://www.gdeltproject.org/"
    }
  ],
  "attributions": [
    {
      "name": "GDELT Project",
      "url": "https://www.gdeltproject.org/"
    }
  ]
}

Every terminal run also writes OUTPUT and RUN_SUMMARY key-value records. COMPLETE means the configured sources produced persisted rows without operational warnings. PARTIAL preserves useful rows alongside source or state diagnostics. VALID_EMPTY describes a successful collection window with no new matching items, and INVALID_INPUT gives an actionable input correction. UPSTREAM_FAILED and CONFIG_ERROR retain the same diagnostics contract for source and configuration follow-up.

API quick start

Use your own Apify token to run the deployed Actor and read its returned dataset.

$curl -X POST "https://api.apify.com/v2/acts/khadinakbar~google-alerts-alternative/run-sync-get-dataset-items" -H "Authorization: Bearer $APIFY_TOKEN" -H "Content-Type: application/json" -d '{"alertId":"ai-company-news","watchQueries":["OpenAI"],"sourceMode":"gdeltOnly","lookbackHours":24,"maxItems":25}'

For a recurring alert, save the input as an Apify task, attach a schedule, and route the task run or dataset to your preferred notification workflow.

AI agent and MCP prompt card

As an AI agent, monitor the supplied watch queries for the stated news window. Return only source-linked alert rows from the Actor dataset, report the terminal outcome from OUTPUT, retain each row's provenance and collection time, observe the maxItems cost cap, and describe the result as current public-news and selected-feed coverage rather than a full-web claim.

The Actor accepts structured JSON input and emits a dataset, OUTPUT, and RUN_SUMMARY; it performs no outbound email delivery. An agent can read the dataset after the run, route new rows where appropriate, and use PARTIAL or VALID_EMPTY as a precise workflow signal.

Workflow scenario: daily brand-news brief

A communications lead starts with a brand and two competitor names, then saves the bounded input as a daily Apify task. The scheduled run queries current public news, merges repeat article URLs, and remembers previously delivered identities for the chosen alert. Next, the lead routes only isNew: true records into an internal brief, while the full source provenance remains available for review. The same workflow can include a selected public trade feed when a topic benefits from a known publisher source.

How this workflow compares with Google Alerts

Decision point	This Actor	Google Alerts
Scope and workflow	Structured public-news and selected-feed collection for explicit queries	Google-managed alert product experience
Billing and cost boundary	Pay per event for validated dataset items plus platform usage	Google product terms and account experience govern its delivery surface
Effective efficiency	A bounded JSON input yields source-linked rows that a downstream workflow can process	Alert emails provide a Google-managed notification format
Output contract	Dataset rows, OUTPUT, and RUN_SUMMARY with source provenance	Google-managed result and alert delivery surfaces
Integrations and automation	Apify API, saved tasks, schedules, datasets, and webhooks	Google alerts integrate through the Google product experience
Freshness and state	Collection timestamps and explicit retained deduplication state	Google manages its own alert evaluation and delivery behavior

This Actor supports a bounded, inspectable news-monitoring workflow. Google Alerts remains the better route for users who prefer the Google alert product and its account-linked delivery surface.

Best results with a focused standalone workflow

This Actor is designed as a focused standalone workflow. Provide specific watch queries, choose a time window that matches the schedule cadence, and set a clear maximum item count. Add selected public feeds when a publisher matters to the monitoring plan, then confirm their applicable terms before scheduling. Treat the returned source URLs and collection times as the scope of each run, and use the dataset as the handoff point for alerts, reports, or review.

Builder's note

I built this workflow around a simple operational need: recurring monitoring is most useful when every retained item has a query label, a source URL, a collection timestamp, and an explicit deduplication decision. My goal was to make that bounded step easy to schedule and easy to connect to another system without overstating it as a replacement for every Google product surface.

Responsible use

Use only public sources you are authorized to collect under applicable laws and source terms. Keep downstream handling aligned with publisher rights and your organization’s policies. GDELT-derived rows carry the required attribution record, and selected-feed rows preserve the source that supplied them.

GDELT Project is an independent third-party data source. This Actor is not affiliated with, associated with, or endorsed by the GDELT Project.

Pricing and run costs

This Actor uses Pay per event plus Apify platform usage. The Pricing tab lists the current event rates and billing terms.

Event	Billing unit	When it applies
apify-actor-start	Actor Start	Charged when the Actor starts running. Number of events charged depends on Actor memory (one event per GB, minimum one event).
alert-item-emitted	Deduplicated alert item emitted	Charged only after one schema-valid, deduplicated article alert item is persisted in the default dataset.

Run cost combines the charged events and Apify platform usage. Review the run charge limit and requested result count before starting.

Connect an AI agent

Use the Apify MCP configurator to choose an available client connection. Inspect this Actor’s current input schema and required credentials before running it.