# RSS & Atom Feed Reader (Bulk Feeds) (`proper_ecosystem_cie/rss-feed-reader`) Actor

Read many RSS, Atom and RDF feeds at once and get clean, normalized items: title, link, publish date (ISO), author, summary, full content, categories and enclosures (podcasts). Filter by date.

- **URL**: https://apify.com/proper_ecosystem_cie/rss-feed-reader.md
- **Developed by:** [Proper Ecosystem Tools](https://apify.com/proper_ecosystem_cie) (community)
- **Categories:** News, Automation
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.50 / 1,000 feed items

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## RSS & Atom Feed Reader (Bulk Feeds)

Read **RSS, Atom, and RDF feeds in bulk** and get clean, consistent items, whatever the feed format. Perfect for news monitoring, content curation, podcast tracking, and feeding AI pipelines.

### Features

- Normalized fields across RSS 0.9x, 1.0, and 2.0, Atom, and RDF
- ISO 8601 UTC dates, HTML-stripped summaries, and full content when available
- Categories and enclosures (podcast audio, images)
- `publishedAfter` filter for new items only, ideal for schedules
- Pay only per item returned

### Input

| Field | Description |
|---|---|
| `feedUrls` | RSS, Atom or RDF feed URLs, one per line. |
| `maxItemsPerFeed` | Newest items first, as ordered by the feed. |
| `publishedAfter` | Only items published after this ISO date, e.g. 2025-01-01. |
| `concurrency` | Items processed in parallel. |

### Output (illustrative example)

```json
{
 "feedTitle": "Example Blog",
 "title": "Example Post Title",
 "link": "https://www.example.com/posts/example",
 "published": "2025-01-15T12:00:00+00:00",
 "author": "Sample Author",
 "categories": [
  "news"
 ]
}
```

### Pricing

Pay per event: **feed item**. Rows that fail with an `error` are free. Set a maximum charge per run to cap spend.

### Use cases

- Monitor news and competitor blogs on a schedule
- Aggregate podcasts and episodes
- Send new items to Slack, email, or a database
- Feed fresh articles to an LLM for summaries

Works with the Apify API, schedules, webhooks, Make, Zapier, n8n, and AI agents via MCP.

# Actor input Schema

## `feedUrls` (type: `array`):

RSS, Atom or RDF feed URLs, one per line.

## `maxItemsPerFeed` (type: `integer`):

Newest items first, as ordered by the feed.

## `publishedAfter` (type: `string`):

Only items published after this ISO date, e.g. 2025-01-01.

## `concurrency` (type: `integer`):

Items processed in parallel.

## Actor input object example

```json
{
  "feedUrls": [
    "https://blog.python.org/feeds/posts/default"
  ],
  "maxItemsPerFeed": 100,
  "concurrency": 10
}
```

# Actor output Schema

## `dataset` (type: `string`):

Dataset with one row per input item

## `runStats` (type: `string`):

Summary counts for the run

# 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 = {
    "feedUrls": [
        "https://blog.python.org/feeds/posts/default"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("proper_ecosystem_cie/rss-feed-reader").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 = { "feedUrls": ["https://blog.python.org/feeds/posts/default"] }

# Run the Actor and wait for it to finish
run = client.actor("proper_ecosystem_cie/rss-feed-reader").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 '{
  "feedUrls": [
    "https://blog.python.org/feeds/posts/default"
  ]
}' |
apify call proper_ecosystem_cie/rss-feed-reader --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,proper_ecosystem_cie/rss-feed-reader"
        }
    }
}
```

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/NgzecUaZnPYbazdPb/builds/lRPLfeoka2peieOhP/openapi.json