News MCP Server
来自美联社、BBC、NPR、黑客新闻和谷歌新闻的实时新闻聚合
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📰 News MCP Server — AP, BBC, NPR, Hacker News & Google News (nexgendata/news-mcp-server) Actor
News monitoring MCP server for AI agents (Claude Desktop, Cursor, OpenAI Agents SDK). Live news search and headlines across AP News, BBC, NPR, Hacker News, and Google News via MCP. Pay per tool call.
- URL: https://apify.com/nexgendata/news-mcp-server.md
- Developed by: NexGenData (community)
- Categories: AI, News, MCP servers
- Stats: 12 total users, 4 monthly users, 100.0% runs succeeded, 0 bookmarks
- User rating: No ratings yet
Pricing
from $10.00 / 1,000 results
This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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.
In JavaScript/TypeScript projects, use official JavaScript/TypeScript client:
npm install apify-client
In Python projects, use official Python client library:
pip install apify-client
In shell scripts, use Apify CLI:
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## 📰 News MCP Server — Real-Time News Monitoring for AI Agents
Connect AI agents to live news through the Model Context Protocol — AP News, BBC, NPR, Hacker News, and Google News. A drop-in **alternative to** NewsAPI ($449/mo) and GDELT — without enterprise contracts.
### Why This MCP Server
| Feature | NexGenData News MCP | NewsAPI | GDELT API |
|---|---|---|---|
| Cost | Pay-per-event, per tool call | $449 - $1,999 / month | Free (heavy quota) |
| AI agent integration | Native MCP — Claude Desktop, Cursor | None | None |
| Coverage | AP, BBC, NPR, Hacker News, Google News | 70K+ sources (English-heavy) | Global news, 100+ languages |
| Real-time | Yes | Yes (paid tiers) | Hourly |
| Auth | Apify token | API key + plan | API key |
| Output format | Structured JSON for LLM tools | JSON | JSON |
| Time-to-first-call | < 60 seconds | Plan signup | API key signup |
Give Claude, ChatGPT, or Cursor live access to AP News, BBC, NPR, Hacker News, and Google News from one tool surface.
### What You Get
Tools exposed to your AI agent:
- **`get_ap_news`** — latest AP News (Associated Press) headlines: titles, summaries, URLs, publication dates
- **`get_bbc_news`** — latest BBC News headlines: titles, summaries, URLs, publication dates
- **`get_npr_news`** — latest NPR (National Public Radio) stories: titles, summaries, URLs
- **`get_hacker_news`** — top Hacker News (Y Combinator) stories: titles, URLs, scores, comment counts
- **`search_google_news`** — keyword search across Google News: headlines, sources, URLs, publication dates
All responses are clean JSON optimized for LLM function-calling.
### Use Cases
- **Brand monitoring agents** — Claude scans AP/BBC/NPR/Google News coverage of a brand on a schedule
- **Equity research bots** — auto-summarize headline news for a ticker before earnings
- **Tech trend tracking** — agents pull top Hacker News stories for startup and tech signal
- **Topic alerts** — search Google News for a keyword and surface fresh coverage
- **Content creators** — agents draft trend-of-the-day posts from live news signal
### Quick Start
Hook this MCP server into Claude Desktop or Cursor and ask in natural language: *"Get the latest AP News headlines and summarize the top three stories."*
Or call a tool programmatically via the Apify API. Each tool returns structured JSON ready for LLM function-calling.
### Related NexGenData Actors
| Use case | Actor |
|----------|-------|
| AP News article scraper | [AP News Scraper](https://apify.com/nexgendata/ap-news-scraper?fpr=2ayu9b) |
| BBC News article scraper | [BBC News Scraper](https://apify.com/nexgendata/bbc-news-scraper?fpr=2ayu9b) |
| NPR story scraper | [NPR Scraper](https://apify.com/nexgendata/npr-scraper?fpr=2ayu9b) |
| Hacker News stories + comments scraper | [Hacker News Scraper](https://apify.com/nexgendata/hacker-news-scraper?fpr=2ayu9b) |
| Finance + market data for AI agents | [Finance MCP Server](https://apify.com/nexgendata/finance-mcp-server?fpr=2ayu9b) |
### FAQ
**Q: Is the news data licensed?**
The server reads publicly available news pages and RSS feeds. For redistribution beyond internal analysis, check the target source's ToS.
**Q: Does it cover non-English news?**
The covered sources (AP, BBC, NPR, Hacker News, Google News) are English-first.
**Q: How fresh is the data?**
Each tool call fetches live data at call time.
**Q: Can the AI agent stream news as it arrives?**
The MCP call pattern is request-response. For streaming, schedule the actor on a webhook and POST to your agent endpoint.
### About NexGenData
NexGenData publishes a large catalog of buyer-intent actors plus a family of MCP servers for AI agent workflows. All pay-per-event. Browse the full catalog at https://apify.com/nexgendata?fpr=2ayu9b
🏠 Home: [thenextgennexus.com](https://thenextgennexus.com)
📦 Full catalog: [apify.com/nexgendata](https://apify.com/nexgendata?fpr=2ayu9b)
# Actor input Schema
## Actor input object example
```json
{}
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
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 = {};
// Run the Actor and wait for it to finish
const run = await client.actor("nexgendata/news-mcp-server").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
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 = {}
# Run the Actor and wait for it to finish
run = client.actor("nexgendata/news-mcp-server").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
CLI example
echo '{}' |
apify call nexgendata/news-mcp-server --silent --output-dataset
MCP server setup
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=nexgendata/news-mcp-server",
"--header",
"Authorization: Bearer <YOUR_API_TOKEN>"
]
}
}
}
OpenAPI specification
{
"openapi": "3.0.1",
"info": {
"title": "📰 News MCP Server — AP, BBC, NPR, Hacker News & Google News",
"description": "News monitoring MCP server for AI agents (Claude Desktop, Cursor, OpenAI Agents SDK). Live news search and headlines across AP News, BBC, NPR, Hacker News, and Google News via MCP. Pay per tool call.",
"version": "0.0",
"x-build-id": "H3dXMagFDHxQDM6uc"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/nexgendata~news-mcp-server/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-nexgendata-news-mcp-server",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/nexgendata~news-mcp-server/runs": {
"post": {
"operationId": "runs-sync-nexgendata-news-mcp-server",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/nexgendata~news-mcp-server/run-sync": {
"post": {
"operationId": "run-sync-nexgendata-news-mcp-server",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}