# Medium Feed Lookup: Latest Posts by Author, Tag, Publication (`accountable_eel/medium-feed-lookup`) Actor

Latest Medium posts for any author, tag or publication from Medium's public RSS feeds: title, date, tags, excerpt and link, with a monitoring mode that returns and bills only posts new since your last run.

- **URL**: https://apify.com/accountable_eel/medium-feed-lookup.md
- **Developed by:** [Adriana Voss](https://apify.com/accountable_eel) (community)
- **Categories:** News, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 post returneds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## Medium Feed Lookup: Latest Posts by Author, Tag, Publication

**Get the latest Medium posts for any author, tag or publication as clean rows, and get alerted to new ones.**
Each feed you list returns its most recent posts with title, link, author, publish and update dates, tags, a text excerpt and the lead image. Turn on monitoring mode and run it on a schedule to receive only the posts that are new since your last run, charged per post and free on a quiet day.

**Who uses it.** Content and competitor-research teams tracking a company's engineering blog, newsletter writers curating a tag, analysts watching which publications cover a topic, and agents or n8n/Clay flows that need "what did this author publish this week" as structured data.

**What it reads.** Medium's own public RSS feeds (`medium.com/feed/@author`, `/feed/tag/<tag>`, `/feed/<publication>`). A feed holds the 10 most recent posts, so this is a latest-posts and new-post alert actor, not an archive scraper. Claps and responses are not in the feed and are not returned. Full text is only in author and publication feeds, so `wordCount` is `null` on tag feeds (never `0`).

### How to use

1. **In the Apify Console.** Open the actor page and click **Start** — the `feeds` field is already pre-filled with a working example. Results land in the run's dataset as soon as each item is found.
2. **Via the API.** Call it directly with a POST request — no Console needed once you have an API token:
   ```bash
   curl "https://api.apify.com/v2/acts/accountable_eel~medium-feed-lookup/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
     -X POST \
     -H "Content-Type: application/json" \
     -d '{"feeds":["@netflixtechblog","tag/data-science"]}'
   ```
3. **On a schedule.** Save this actor as an Apify **Task** with the input you want, then add a **Schedule** (hourly, daily, weekly) so it runs on its own — no server of your own required.

### Input

```json
{
  "feeds": [
    "@netflixtechblog",
    "tag/data-science"
  ]
}
```

One per line: an author (@netflixtechblog), a tag (tag/data-science) or a publication (towards-data-science). A medium.com profile, tag, publication or feed URL works too. Each feed returns its latest posts, newest first. Accepted formats: @netflixtechblog, tag/data-science, towards-data-science, https://medium.com/@netflixtechblog.

One feed per line. A bare word is read as a publication slug (`towards-data-science`); put `@` in front for an author and `tag/` in front for a tag. Medium profile, tag, publication and feed URLs are accepted and reduced to the same three forms. Custom-domain publications are reached by their Medium slug.

### Output

One row per item, for example:

| query | found | status | feed | feedType | feedTitle | feedUrl | postCount | truncated | monitorStatus | posts | postId | title | url | author | publishedAt | updatedAt | tags | excerpt | imageUrl | wordCount | isNew | firstSeenAt | scrapedAt |
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- |
| @netflixtechblog | true | OK | <feed> | <feed type> | <feed title> | <feed url> | <posts returned> | <more posts than the cap> | <monitoring status> | \<all posts (full list)> | <post id> | <post title> | <post url> | <author> | <published on> | <last updated> | <tags> | <excerpt> | <lead image> | <word count> | \<is this post new?> | <first seen on a run> | 1970-01-01T00:00:00.000Z |

Example rows (real output, trimmed):

```json
{
  "query": "tag/data-science",
  "found": true,
  "status": "OK",
  "feed": "tag/data-science",
  "feedType": "tag",
  "feedTitle": "Data Science on Medium",
  "postCount": 10,
  "postId": "bcfe74cd8d1a",
  "title": "When AI Is Unsure: Rethinking Health Misinformation Detection in Nigerian Pidgin",
  "url": "https://medium.com/@destinifeoluwa/when-ai-is-unsure-rethinking-health-misinformation-detection-in-nigerian-pidgin-bcfe74cd8d1a",
  "author": "Olayode Racheal Oluwayemisi",
  "publishedAt": "2026-10-11T16:45:34.000Z",
  "tags": ["healthtech", "research", "data", "data-science"],
  "excerpt": "Why reliable AI should know when to make a prediction and when to step back.",
  "wordCount": null,
  "isNew": null,
  "scrapedAt": "2026-10-11T17:00:00.000Z"
}
```

A feed that does not exist comes back as a row with `"found": false` (`NOT_FOUND`) and is never charged. A quiet monitoring run returns one row with `"postCount": 0` and is never charged either.

### Pricing

**$4 per 1,000 posts on the Free plan**, less on paid plans, plus a $0.00005 start fee per run. You pay only for posts actually returned.

Pay-per-event. A flat per-run fee covers session/proxy warmup; you're billed
per item only when data is actually found and returned — see
`.actor/pay_per_event.json` for exact prices. A miss is never charged.

### Example runs

Paste any of these into the Input tab and press Start. All three return rows with no key, no token
and no account of your own beyond an Apify login.

**Latest posts from one company engineering blog.**

```json
{
  "feeds": ["@netflixtechblog"],
  "maxItems": 5
}
```

**A tag and a publication side by side.**

```json
{
  "feeds": ["tag/data-science", "towards-data-science"]
}
```

**New-post alert: schedule this daily and only new posts come back.**

```json
{
  "feeds": ["@netflixtechblog", "tag/machine-learning"],
  "onlyNewSinceLastRun": true,
  "deltaName": "my-medium-alerts"
}
```

### Use it from Clay, n8n, Make, or an AI agent

This actor runs synchronously over plain HTTP — call it directly from a script, a workflow tool, or an AI agent, no Apify Console needed once you have an API token.

```bash
curl "https://api.apify.com/v2/acts/accountable_eel~medium-feed-lookup/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
  -X POST \
  -H "Content-Type: application/json" \
  -d '{"feeds":["@netflixtechblog","tag/data-science"]}'
```

**n8n.** Add an HTTP Request node: Method `POST`, URL `https://api.apify.com/v2/acts/accountable_eel~medium-feed-lookup/run-sync-get-dataset-items?token=<YOUR_TOKEN>`, Body Content Type `JSON`, JSON Body `{"feeds":["@netflixtechblog","tag/data-science"]}` (swap in an expression from an earlier node for a real value).

**Clay.** Add an "HTTP API" column: Method `POST`, URL `https://api.apify.com/v2/acts/accountable_eel~medium-feed-lookup/run-sync-get-dataset-items?token=<YOUR_TOKEN>`, Body `{"feeds":["{{feed}}"]}`, mapping the row's feed into the `feeds` array.

**MCP.** In Claude, Cursor, or any MCP client with the Apify MCP server, ask for "medium scraper by author or tag" — the agent will find and run this actor.

# Actor input Schema

## `feeds` (type: `array`):

One per line: an author (@netflixtechblog), a tag (tag/data-science) or a publication (towards-data-science). A medium.com profile, tag, publication or feed URL works too. Each feed returns its latest posts, newest first. Accepted formats: @netflixtechblog, tag/data-science, towards-data-science, https://medium.com/@netflixtechblog. You're only charged for the ones we actually find — a miss costs nothing.

## `testRun` (type: `boolean`):

Turn this on to test your input on a small sample before running the full list. Turn it off to process everything.

## `onlyFound` (type: `boolean`):

Only keep rows where something was actually found. Misses are always free, whether or not you show them here.

## `includeKeywords` (type: `array`):

Optional. Only keep results that mention at least one of these words (e.g. a job title, a city, a product name). Leave empty to keep everything.

## `excludeKeywords` (type: `array`):

Optional. Drop any result that mentions one of these words. Leave empty to skip nothing.

## `maxResults` (type: `integer`):

Optional. Stop the run once this many results have been found — useful for a quick, cheap sample. Leave blank for no limit.

## `maxItems` (type: `integer`):

A Medium feed carries its 10 most recent posts, so 10 is the most a feed can return; lower it to cap what you pay per feed. Up to 50 is accepted for forward compatibility.

## `onlyNewSinceLastRun` (type: `boolean`):

On: only posts not seen on your previous run of the same feed are returned and charged for. Run this on a schedule as a new-post alert. Off: every post in the feed is returned every time.

## `deltaName` (type: `string`):

Optional. Names the monitoring memory so two schedules of this actor stay apart, or one memory survives an input change. Each feed keeps its own record inside it. Leave empty to use the default watchlist.

## `columns` (type: `array`):

Choose which pieces of information to include in each result row. All are included by default.

## `expandRows` (type: `boolean`):

When on, each post found gets its own row instead of being grouped under its feed. You're still only charged once per feed, no matter how many rows it produces.

## `maxConcurrency` (type: `integer`):

Parallel requests. Keep conservative — this target has no browser fallback, so getting blocked costs more than slow-and-steady.

## Actor input object example

```json
{
  "feeds": [
    "@netflixtechblog",
    "tag/data-science"
  ],
  "testRun": false,
  "onlyFound": false,
  "includeKeywords": [],
  "excludeKeywords": [],
  "maxItems": 10,
  "onlyNewSinceLastRun": false,
  "deltaName": "",
  "columns": [
    "feed",
    "feedType",
    "feedTitle",
    "feedUrl",
    "postCount",
    "truncated",
    "monitorStatus",
    "posts",
    "postId",
    "title",
    "url",
    "author",
    "publishedAt",
    "updatedAt",
    "tags",
    "excerpt",
    "imageUrl",
    "wordCount",
    "isNew",
    "firstSeenAt"
  ],
  "expandRows": true,
  "maxConcurrency": 2
}
```

# 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 = {
    "feeds": [
        "@netflixtechblog",
        "tag/data-science"
    ],
    "includeKeywords": [],
    "excludeKeywords": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("accountable_eel/medium-feed-lookup").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 = {
    "feeds": [
        "@netflixtechblog",
        "tag/data-science",
    ],
    "includeKeywords": [],
    "excludeKeywords": [],
}

# Run the Actor and wait for it to finish
run = client.actor("accountable_eel/medium-feed-lookup").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 '{
  "feeds": [
    "@netflixtechblog",
    "tag/data-science"
  ],
  "includeKeywords": [],
  "excludeKeywords": []
}' |
apify call accountable_eel/medium-feed-lookup --silent --output-dataset

```

## MCP server setup

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

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/uvwtKiB51zCbyUBHa/builds/FhPi6YbcIOl5f81Rl/openapi.json