# RSS to JSON API — RSS, Atom & JSON Feed Parser (`rtworule/public-feed-normalizer`) Actor

Parse public RSS, Atom, and JSON feeds into one stable dataset and API. Filter items and optionally emit only new content across scheduled runs.

- **URL**: https://apify.com/rtworule/public-feed-normalizer.md
- **Developed by:** [Kunteper Koyu](https://apify.com/rtworule) (community)
- **Categories:** News, Automation, Developer tools
- **Stats:** 2 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1.00 / 1,000 feed item normalizeds

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/platform/actors/running/actors-in-store#pay-per-event

## 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

## RSS to JSON API — RSS, Atom & JSON Feed Parser

Turn many public RSS 2.0, Atom, and JSON Feed URLs into one stable JSON dataset. Use this feed parser and RSS-to-JSON API for news monitoring, content pipelines, RAG ingestion, alerts, aggregation, and scheduled change detection.

### Why use it

- one normalized schema across RSS, Atom, and JSON Feed
- bulk feed input with bounded concurrency
- keyword and publication-date filters
- deterministic SHA-256 fingerprints for deduplication
- persistent incremental mode that emits and charges only unseen items
- configurable per-feed and total result limits
- safe public-URL validation and bounded downloads

### Common use cases

- aggregate company blogs, news, podcasts, or industry sources
- create a filtered news-monitoring or alert pipeline
- normalize content before RAG ingestion or summarization
- convert RSS/Atom to JSON for an application or automation
- schedule runs and detect new or changed items by fingerprint

### Quick start

1. Click **Try for free** or **Run**.
2. Add public RSS, Atom, or JSON Feed URLs.
3. Optionally add search terms or a publication cutoff.
4. Run the Actor and consume the normalized dataset.

```json
{
  "feedUrls": ["https://blog.apify.com/rss/"],
  "searchTerms": ["AI", "automation"],
  "publishedAfter": "2026-01-01",
  "maxItemsPerFeed": 100,
  "maxItemsTotal": 1000,
  "concurrency": 5,
  "timeoutSeconds": 30,
  "incrementalMode": true,
  "incrementalFirstRun": "baselineOnly",
  "incrementalStoreName": "my-news-monitor",
  "seenRetentionDays": 90
}
```

#### New-items-only scheduled runs

Set `incrementalMode` to `true` and reuse the same `incrementalStoreName` across runs. On the first run, `incrementalFirstRun: "baselineOnly"` remembers current items without emitting or charging them as result events; `"emitAll"` delivers the current backlog. Later runs emit only fingerprints not already stored. `seenRetentionDays` and `maxSeenItems` bound the history, so expired or evicted items can appear again. Use a different store name for every independent monitor and avoid overlapping runs that write to the same store.

### Example result

```json
{
  "feedUrl": "https://blog.apify.com/rss/",
  "feedTitle": "Apify Blog",
  "feedType": "rss",
  "itemId": "https://blog.apify.com/example-post/",
  "title": "Example post",
  "url": "https://blog.apify.com/example-post/",
  "author": "Apify",
  "summary": "A normalized feed item summary.",
  "publishedAt": "2026-07-01T12:00:00.000Z",
  "categories": ["automation"],
  "fingerprint": "a-stable-sha256-fingerprint",
  "retrievedAt": "2026-07-11T12:00:00.000Z"
}
```

The values above illustrate the output schema; live fields depend on each publisher's feed.

### Run by API

Set `APIFY_TOKEN` in your environment and keep it secret.

#### cURL

```bash
curl -X POST \
  "https://api.apify.com/v2/acts/rtworule~public-feed-normalizer/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"feedUrls":["https://blog.apify.com/rss/"],"maxItemsTotal":20,"incrementalMode":true,"incrementalStoreName":"my-apify-blog-monitor"}'
```

#### JavaScript

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

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('rtworule/public-feed-normalizer').call({
  feedUrls: ['https://blog.apify.com/rss/'],
  maxItemsTotal: 20,
  incrementalMode: true,
  incrementalStoreName: 'my-apify-blog-monitor',
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);
```

#### Python

```python
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run = client.actor("rtworule/public-feed-normalizer").call(run_input={
    "feedUrls": ["https://blog.apify.com/rss/"],
    "maxItemsTotal": 20,
    "incrementalMode": True,
    "incrementalStoreName": "my-apify-blog-monitor",
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)
```

### Pricing

This Actor uses pay per event. A `feed-item-normalized` event costs **$0.001 per stored item**: 100 delivered items cost $0.10 and 1,000 cost $1.00 in event charges. Apify applies a **$0.01 minimum run charge**. Filters, result limits, and incremental mode help control output; the Actor also respects the run's maximum total charge. Incremental mode does not emit or charge previously remembered items as result events.

### Integrations and automation

- schedule a Task with `incrementalMode: true` to emit only unseen items
- send new rows to Slack, email, Make, Zapier, n8n, or a webhook
- load normalized content into a vector database, CMS, warehouse, or search index
- export CSV/XLSX to Sheets for a lightweight editorial dashboard
- use `publishedAfter` to limit recurring runs to a recent window

### FAQ and troubleshooting

**Does it discover feed URLs from a website homepage?** No. Supply the direct public RSS, Atom, or JSON Feed URL.

**How do I avoid processing the same item twice?** Enable `incrementalMode` and reuse one unique `incrementalStoreName` for that monitoring stream. Choose `baselineOnly` on the first run to remember current items without emitting them, or `emitAll` to deliver the current backlog. You can also deduplicate downstream by `fingerprint` or `itemId`.

**Can an old item appear again?** Yes, after its fingerprint exceeds `seenRetentionDays` or the state exceeds `maxSeenItems`. Increase those bounds when a longer history matters.

**Why are some fields empty?** Feed standards allow publishers to omit author, summary, content, categories, or timestamps. The Actor does not invent missing source data.

**Why was a feed rejected?** The URL must be public HTTP/HTTPS without embedded credentials. Private, local, reserved, and metadata-service destinations are blocked, including redirects.

**Why did parsing fail?** Confirm the URL returns valid RSS, Atom, or JSON Feed rather than an HTML page. Publisher format errors and responses over 5 MB cannot be normalized.

### Responsible use, limitations, and support

The Actor follows at most five validated public redirects, caps each response at 5 MB, and does not bypass authentication. Feed formats and publisher policies vary. Users are responsible for permission to access and reuse feed content, copyright obligations, retention, and downstream processing.

For an unexpected result from a valid public feed, open an issue from the Actor page with the run ID, feed URL, feed type, and expected behavior. Never include credentials or private feeds.

### More tools from this developer

- [Greenhouse, Lever & Ashby Jobs Scraper API](https://apify.com/rtworule/public-ats-job-feed-normalizer)
- [Bulk URL Status Checker & Redirect Audit](https://apify.com/rtworule/bulk-url-health-auditor)
- [Website Tech Stack Detector](https://apify.com/rtworule/bulk-website-tech-detector)
- [AI Search Readiness / GEO & AEO Auditor](https://apify.com/rtworule/ai-search-readiness-auditor)

# Actor input Schema

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

Public RSS, Atom, or JSON Feed URLs. Private network destinations are rejected.

## `searchTerms` (type: `array`):

Keep items containing at least one term in title, summary, or content. Empty means all items.

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

Optional ISO date or timestamp.

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

Maximum normalized items to retain from each feed.

## `maxItemsTotal` (type: `integer`):

Maximum normalized items to retain across all feeds.

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

Number of public feeds to fetch at the same time.

## `timeoutSeconds` (type: `integer`):

Maximum seconds to wait for each feed response.

## `incrementalMode` (type: `boolean`):

Remember delivered fingerprints in a named key-value store and emit/charge only items not seen by earlier runs.

## `incrementalFirstRun` (type: `string`):

Emit all current items, or save them as a baseline without emitting or charging them.

## `incrementalStoreName` (type: `string`):

Persistent store used for seen fingerprints. Use a unique name for each independent monitor or scheduled task.

## `seenRetentionDays` (type: `integer`):

Forget fingerprints older than this many days. A forgotten item can be emitted again if it remains in a feed.

## `maxSeenItems` (type: `integer`):

Bounds persistent state. Least-recently-recorded fingerprints are removed first and may later be emitted again.

## Actor input object example

```json
{
  "feedUrls": [
    "https://blog.apify.com/rss/"
  ],
  "searchTerms": [],
  "publishedAfter": "",
  "maxItemsPerFeed": 100,
  "maxItemsTotal": 1000,
  "concurrency": 5,
  "timeoutSeconds": 30,
  "incrementalMode": false,
  "incrementalFirstRun": "emitAll",
  "incrementalStoreName": "public-feed-normalizer-seen",
  "seenRetentionDays": 90,
  "maxSeenItems": 50000
}
```

# Actor output Schema

## `results` (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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("rtworule/public-feed-normalizer").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("rtworule/public-feed-normalizer").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

```bash
echo '{}' |
apify call rtworule/public-feed-normalizer --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=rtworule/public-feed-normalizer",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/JPmtrS9akoMCwsEGA/builds/lSAcgHH3QqnyXVh13/openapi.json