# Mastodon Trending Posts and Hashtags Radar (`adaptive_nightmare/mastodon-trending-radar`) Actor

Extract Mastodon Trending Posts and Hashtags data in clean JSON or CSV. Query by limit, server for records, engagement metrics, and metadata. Export datasets, run via API or Python/Node.js SDK, schedule runs, or integrate with webhooks with zero proxy fees.

- **URL**: https://apify.com/adaptive_nightmare/mastodon-trending-radar.md
- **Developed by:** [Darim Quraishi](https://apify.com/adaptive_nightmare) (community)
- **Categories:** Social media, News, AI
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$0.85 / 1,000 results

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

## Mastodon Trending Posts and Hashtags Radar

Extract trending public Fediverse posts, viral hashtags, reply counts, reblogs, and author handles from Mastodon instances without API keys.

### Features

- Scrapes the official Mastodon trends endpoint tracking the fastest growing conversations across the decentralized Fediverse.
- Captures sanitized post text, author profile handles, follower counts, community reblogs, and favorite counts.
- Gathers trending hashtag arrays and attached media asset links.
- Operates via public REST endpoints with zero authentication tokens and zero proxy overhead.
- Delivers clean structured records formatted for export to JSON, CSV, Excel, or automated social media listening pipelines.

### Input parameters

- Maximum Posts: Number of trending posts to collect, from 5 to 100. Default is 25.
- Mastodon Server Instance: Mastodon instance domain name. Default is mastodon.social.

### Output dataset fields

Each dataset record contains:

- id: Unique Mastodon status identifier.
- url: Permanent web link to the status on the instance.
- authorUsername: Creator account username.
- authorDisplayName: Public profile display name.
- authorAcct: Complete Fediverse handle.
- authorFollowersCount: Author network follower metric.
- content: Plain text post content with HTML tags removed.
- reblogsCount: Total community shares and reblogs.
- favouritesCount: Total community stars and favorites.
- repliesCount: Total comment thread replies.
- language: ISO language tag.
- tags: Array of attached hashtag topics.
- mediaUrls: Array of image or media asset links.
- createdAt: ISO formatted publication timestamp.
- scrapedAt: UTC timestamp when the data was extracted.

### Use cases

- Social listening: Track breaking news and emerging cultural discussions across open source decentralized social networks.
- Sentiment analysis: Ingest public opinion streams on technology and policy topics without restrictive platform quotas.
- Creator discovery: Identify influential voices and fast growing authors on the decentralized web.

# Actor input Schema

## `limit` (type: `integer`):

Maximum number of trending posts to collect.

## `server` (type: `string`):

Mastodon host domain instance.

## Actor input object example

```json
{
  "limit": 25,
  "server": "mastodon.social"
}
```

# 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("adaptive_nightmare/mastodon-trending-radar").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("adaptive_nightmare/mastodon-trending-radar").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 '{}' |
apify call adaptive_nightmare/mastodon-trending-radar --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,adaptive_nightmare/mastodon-trending-radar"
        }
    }
}
```

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/0VnsjfdzZRI1ll0D9/builds/EiDKygcUAmXI7BA5T/openapi.json