# Reddit Subreddit Finder — Community Discovery ✅ (`nexascout/reddit-subreddit-finder`) Actor

Discover Reddit communities by topic. Compare name and description matches, review weekly activity estimates, and export ranked subreddit links with search coverage.

- **URL**: https://apify.com/nexascout/reddit-subreddit-finder.md
- **Developed by:** [NexaScout](https://apify.com/nexascout) (community)
- **Categories:** Social media, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

from $250.00 / 1,000 community search-page attempts

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

## Reddit Subreddit Finder — Community Discovery

Find Reddit communities related to your topic and export a ranked list with original links, descriptions and available weekly activity estimates. Use it for audience research, community discovery, content planning and identifying discussions to review.

### Quick start

1. Enter topics such as `hiking` and `camping`.
2. Choose a maximum result count and match threshold.
3. Set a spending limit. Start with a **$3 maximum charge** for two topics.
4. Run the Actor, open **Overview**, then check the coverage summary in `OUTPUT`.

```json
{
  "topics": ["hiking", "camping"],
  "maxResults": 25,
  "minRelevance": 50,
  "maxRunSeconds": 240,
  "region": "US"
}
```

The result count is a maximum, not a guaranteed number. The Actor reads the available community search cards, up to 30 per topic; it does not promise an exhaustive directory.

### Matching and ranking

- **100:** the community name contains the full topic after spaces and punctuation are removed.
- **50:** the description contains the topic phrase.
- **0:** no supported name or description match; these communities are excluded.

For example, `machine learning` can match `r/machinelearning`. Matching is a text-based signal, not a semantic or AI relevance score. Synonyms are not inferred. Use English or Latin-alphabet topics with at least two letters/numbers; non-Latin-only or punctuation-only topics have no supported match.

Set `minRelevance` to **100** for name matches only, or **50** to include description matches. The default **0** also excludes unrelated communities. Rows rank by relevance, then weekly visitors. Communities found under several topics appear once, with those sources in `discoveredIn`.

### Inputs

| Input | Default | Meaning |
| --- | --- | --- |
| `topics` | Required | Up to 20 unique search topics |
| `maxResults` | 50 | Maximum saved communities, from 1 to 200 |
| `minRelevance` | 0 | Match threshold, from 0 to 100 |
| `region` | US | Access location: US, DE, GB, FR, CA or AU |
| `maxRunSeconds` | 240 | Collection budget after initialization, from 30 to 900 seconds |

`region` does not filter communities or authors by country. Startup and cleanup add to total run time. Time and spending limits can stop collection before all topics are searched.

### Output

| Field | Meaning |
| --- | --- |
| `name`, `url` | Subreddit name and original community link |
| `description` | Available description from the search result |
| `weeklyVisitors` | Displayed weekly visitor estimate |
| `weeklyContributions` | Displayed weekly contribution estimate |
| `relevanceScore` | Best supported topic match: 50 or 100 |
| `nicheConfidence` | `high` for name match, `medium` for description match |
| `discoveredIn` | Topics whose search results contained the community |
| `observedAt` | Observation timestamp |

Weekly metrics describe the displayed activity period. Values abbreviated as K/M are rounded estimates; missing values remain `null`. These are not subscriber or member counts.

Dataset views:

- **Overview:** ranked matches, activity, descriptions and links.
- **Community activity:** weekly visitor/contribution estimates.
- **Topics & descriptions:** match sources, descriptions and observation time.

The `OUTPUT` record contains searched sources, unavailable/stopped/no-match topics, filters, emitted counts and billing counters. **PARTIAL** means a time or spending limit stopped work; saved rows remain usable. The platform run may still show success because those rows were finalized correctly.

Unconfirmed empty pages, recognized errors and access blocks are reported as unavailable. A confirmed no-results page, or loaded results with no relevant communities, can correctly produce zero rows. Review coverage before treating a scan as complete.

### Pricing

| Event | Price |
| --- | ---: |
| Run start | $0.05 per GB of memory, minimum one GB |
| Community search-page attempt | $0.25 |
| Unique community saved to this run dataset | $0.02 |

At the default **2 GB**, the start fee is **$0.10**. Every attempted topic search is charged before navigation, including retries, blocked pages and attempts that produce no matching communities. Browser resource files are not separate events.

A community saved once in a run is charged once. Saving it again in a later run is charged again. Examples without retries, using default memory:

- Two search pages and 25 saved communities: **$1.10**.
- Two search pages and 10 saved communities: **$0.80**.
- One search page and zero saved communities: **$0.35**.

These are billing examples, not guarantees of coverage or result count. The minimum maximum charge is **$0.40**; a small cap can stop output after only a few rows. A **$3** cap gives more room for the two-topic example and retries. The Actor checks spending before search navigation and dataset writes.

### API and integrations

Use immutable Actor ID `BJcMldaDqWuL2p8a6` so integrations remain stable if the Store name changes:

```http
POST https://api.apify.com/v2/actors/BJcMldaDqWuL2p8a6/runs?maxTotalChargeUsd=3
Authorization: Bearer YOUR_APIFY_TOKEN
Content-Type: application/json
```

Send the quick-start JSON as the request body, then poll the returned run ID:

```http
GET https://api.apify.com/v2/actor-runs/RUN_ID
Authorization: Bearer YOUR_APIFY_TOKEN
```

Read rows and coverage from the returned default storage IDs:

```http
GET https://api.apify.com/v2/datasets/DATASET_ID/items?clean=true&format=json
GET https://api.apify.com/v2/key-value-stores/KEY_VALUE_STORE_ID/records/OUTPUT
Authorization: Bearer YOUR_APIFY_TOKEN
```

Schedule repeated discovery in Apify or connect exports to your database and automation tools.

This independent research tool is not affiliated with Reddit.

# Actor input Schema

## `topics` (type: `array`):

Up to 20 unique topics. Matching uses Latin letters and numbers; use English or Latin-alphabet topics such as hiking or machine learning.

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

Hard cap on emitted subreddits.

## `minRelevance` (type: `number`):

0 or 50 includes name and description matches; 100 keeps name matches only. Unrelated communities are always excluded.

## `region` (type: `string`):

Access location for the search. It does not filter communities or authors by country.

## `maxRunSeconds` (type: `integer`):

Collection budget after initialization. Startup and cleanup add to total time. Saved rows remain available if collection stops early.

## Actor input object example

```json
{
  "topics": [
    "hiking",
    "machine learning"
  ],
  "maxResults": 50,
  "minRelevance": 0,
  "region": "US",
  "maxRunSeconds": 240
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `summary` (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 = {
    "topics": [
        "hiking",
        "machine learning"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("nexascout/reddit-subreddit-finder").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 = { "topics": [
        "hiking",
        "machine learning",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("nexascout/reddit-subreddit-finder").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 '{
  "topics": [
    "hiking",
    "machine learning"
  ]
}' |
apify call nexascout/reddit-subreddit-finder --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,nexascout/reddit-subreddit-finder"
        }
    }
}
```

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/BJcMldaDqWuL2p8a6/builds/OOzX4ZlgYo2OMwbdG/openapi.json