# Reddit Research Agent (`agenticscraper/reddit-research-agent`) Actor

Give the agent a research task, choose your preferred language model, and receive results in the JSON format you define.

- **URL**: https://apify.com/agenticscraper/reddit-research-agent.md
- **Developed by:** [Agentic Scraper](https://apify.com/agenticscraper) (community)
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.00 / 1,000 llm usages

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 Research Agent

Turn a question into a Reddit research task, choose the language model you want to use, and receive the results in the JSON format you define. You can use it to find discussions, summarize opinions, compare viewpoints, and collect structured insights from public Reddit content.

### Quick start on Apify

1. Open the **Input** tab.
2. Enter a research task, or use the example below.
3. Select a model, or use the default automatic selection.
4. Define the JSON structure you want in the response and adjust the limits if needed.
5. Click **Start**. The result is written to the run’s default dataset.

You can run your own research tasks directly from Apify without changing the source code.

### Example: WordPress discussions in the last 24 hours

```json
{
  "task": "Research discussions about WordPress posted on Reddit in the last 24 hours. Identify the main themes, summarize the most useful insights in English, and include links to the relevant posts.",
  "output_schema": {"type":"object","properties":{"summary":{"type":"string"},"key_themes":{"type":"array","items":{"type":"string"}},"sources":{"type":"array","items":{"type":"string"}}},"required":["summary","key_themes","sources"]},
  "max_tokens": 1200,
  "max_api_calls": 10
}
```

### Input parameters

| Parameter | Type | Default | Description |
|---|---|---:|---|
| `task` | string | — | Your research instruction. Required. Include the topic, time range, subreddit, language, and type of analysis you want. |
| `model` | select | `auto` | The language model used to produce the answer. Choose a specific model or let the Actor select one automatically. |
| `output_schema` | object | `{ "type": "object" }` | The JSON Schema that defines the format of the answer. |
| `max_tokens` | integer | `3000` | Maximum length of the generated answer; allowed range `128–16000`. Larger values may increase the run cost. |
| `max_api_calls` | integer | `5` | Maximum number of searches the Actor can perform; allowed range `1–10`. |

#### Output schema example

```json
{
  "type": "object",
  "properties": {"summary": {"type": "string"}},
  "required": ["summary"]
}
```

### Choosing a model

The model list is refreshed over time. Choose a model based on the balance you want between speed, answer quality, and cost, or select the automatic option for a general-purpose choice.

### Billing

This is a pay-per-event Actor. Your run cost depends on the amount of research performed and the model you select. The active event price and maximum run charge are shown in the Pricing tab.

- Research actions are charged according to the active event price.
- More complex tasks, longer answers, and higher limits may increase the total cost.
- Review the Pricing tab before starting a run to see the current price and maximum run charge.

### Data access and safety

The Actor only researches publicly available Reddit content. It cannot post, comment, vote, send direct messages, or access private account information.

### Limitations

- Results depend on Reddit availability, indexing, deleted content, and the selected model.
- `max_api_calls` limits the number of research searches, not the number of posts returned by a single search.
- Very large results can increase the run cost; focused tasks are recommended.

# Actor input Schema

## `task` (type: `string`):

Question or research task.

## `model` (type: `string`):

Any model ID from GET /models. Defaults to OpenRouter Auto Router.

## `output_schema` (type: `object`):

JSON schema for the research response.

## `max_tokens` (type: `integer`):

Maximum number of generated tokens.

## `max_api_calls` (type: `integer`):

Hard maximum number of MCP tool calls per run.

## Actor input object example

```json
{
  "model": "openrouter/auto",
  "output_schema": {
    "type": "object"
  },
  "max_tokens": 3000,
  "max_api_calls": 5
}
```

# 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("agenticscraper/reddit-research-agent").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("agenticscraper/reddit-research-agent").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 agenticscraper/reddit-research-agent --silent --output-dataset

```

## MCP server setup

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

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/dIk9XbhBkxKwqGXBC/builds/AuxasKCbXctZGqZKy/openapi.json