# GDELT Cloud Intelligence BYOK (`smart_tech_resources/gdelt-news`) Actor

Fetch GDELT Cloud Stories, Events, and Entities with your own API key and output normalized, AI-ready intelligence data for monitoring and research.

- **URL**: https://apify.com/smart\_tech\_resources/gdelt-news.md
- **Developed by:** [Smart Tech Resources](https://apify.com/smart_tech_resources) (community)
- **Categories:** AI, Developer tools, News
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## GDELT Cloud Intelligence BYOK

Collect and normalize GDELT Cloud Stories, Events, and Entities using the user provided API key.

### Input

The input form is defined in `.actor/input_schema.json`. API key fields, where present, use Apify `isSecret: true`.

GDELT Cloud requires your own GDELT Cloud API key. This Actor does not include GDELT Cloud API credits.

### Bring Your Own API Key (BYOK)

This Actor does not include third-party API credits. You must provide your own GDELT Cloud API key.

You are responsible for any third-party API usage fees. This Actor charges only for data processing, normalization, deduplication, enrichment, and Apify dataset/report generation.

### Content types

Use the `contentTypes` input to choose the GDELT Cloud records to collect:

- `stories` for clustered narrative Stories with top article evidence.
- `events` for structured incident-level Events with categories, geography, metrics, and top article evidence.
- `entities` for linked people and organizations connected to Stories and Events.
- `all` to collect Stories, Events, and Entities in one mixed run.

Selecting multiple content types creates a mixed output. Each dataset item includes `contentType` and `gdeltCloudId` so downstream workflows can separate records.

### Output

Each dataset item follows the normalized Global News Intelligence article shape:

- `sourcePlatform`
- `sourceName`
- `title`
- `url`
- `publishedAt`
- `description`
- `content`
- `author`
- `imageUrl`
- `country`
- `language`
- `category`
- `keywords`
- `sentiment`
- `entities`
- `contentType`
- `gdeltCloudId`
- `significance`
- `articleCount`
- `raw`

The key-value store record `SUMMARY` contains counts by source, publisher, country, language, category, sentiment, and date.

### Local run

```bash
apify run
```

Fill the required GDELT Cloud API key in Apify before running against the provider. Do not place real API keys in source code, README examples, GitHub, public Apify examples, logs, or dataset output.

# Actor input Schema

## `gdeltCloudApiKey` (type: `string`):

Required. Use your own GDELT Cloud API key. This value is stored as an Apify secret input.

## `query` (type: `string`):

Free-text semantic search passed to GDELT Cloud.

## `contentTypes` (type: `array`):

Choose one content type, multiple content types for a mixed run, or All to collect Stories, Events, and Entities.

## `fromDate` (type: `string`):

Inclusive start date in YYYY-MM-DD format. GDELT Cloud explicit windows may not exceed 30 days.

## `toDate` (type: `string`):

Inclusive end date in YYYY-MM-DD format. GDELT Cloud explicit windows may not exceed 30 days.

## `dateRange` (type: `string`):

Convenience date range if exact dates are not supplied.

## `country` (type: `string`):

Optional plain-English country filter, for example United States, Malaysia, or South Korea.

## `region` (type: `string`):

Optional plain-English region filter, for example Middle East, South Asia, or Europe.

## `continent` (type: `string`):

Optional continent filter, for example Africa, Asia, Europe, North America, South America, or Oceania.

## `category` (type: `string`):

Optional GDELT Cloud Event category filter, for example Battles, Protests, INFRASTRUCTURE, CRIME, or POLITICAL.

## `subcategory` (type: `string`):

Optional more specific Event subtype. Requires a compatible category.

## `sort` (type: `string`):

GDELT Cloud ranking mode.

## `maxArticles` (type: `integer`):

Maximum normalized records to output across selected content types.

## Actor input object example

```json
{
  "query": "attacks on energy infrastructure",
  "contentTypes": [
    "stories",
    "events"
  ],
  "dateRange": "last_7_days",
  "sort": "significance",
  "maxArticles": 50
}
```

# Actor output Schema

## `articles` (type: `string`):

No description

## `summary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "attacks on energy infrastructure"
};

// Run the Actor and wait for it to finish
const run = await client.actor("smart_tech_resources/gdelt-news").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "query": "attacks on energy infrastructure" }

# Run the Actor and wait for it to finish
run = client.actor("smart_tech_resources/gdelt-news").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "query": "attacks on energy infrastructure"
}' |
apify call smart_tech_resources/gdelt-news --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,smart_tech_resources/gdelt-news"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/N0w2sT0gFXlEHXqfF/builds/mmcfZMtmOHYI8iZmd/openapi.json