# Reddit Scraper MCP (`red.cars/reddit-scraper-mcp`) Actor Reddit MCP for AI agents. Programmatic access to subreddit info, posts, comments, and search. Built for sentiment analysis, community intelligence, and market research. - **URL**: https://apify.com/red.cars/reddit-scraper-mcp.md - **Developed by:** [AutomateLab](https://apify.com/red.cars) (community) - **Categories:** AI, Automation, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## Reddit Scraper MCP AI-native Reddit API for autonomous workflows. Programmatic access to subreddit info, posts, comments, and search. ### Tools | Tool | Description | Price | |------|-------------|-------| | `get_subreddit_info` | Get subreddit metadata — name, title, description, subscribers, active users, creation date, NSFW flag | $0.03 | | `get_posts` | Get posts from any subreddit with sorting (hot/new/top/rising) | $0.03 | | `get_comments` | Get comments from a Reddit post | $0.05 | | `search_reddit` | Search Reddit for posts matching a query with time and sort filters | $0.05 | ### Use Cases - **Sentiment analysis** — monitor community reactions to products, brands, events - **Market research** — discover trending topics, user discussions, pain points - **Competitive intelligence** — track discussions about competitors - **Content inspiration** — find viral posts, trending discussions in any niche - **Academic research** — gather Reddit data for social science research ### API #### MCP Protocol (Standby Mode) Start with `initialize`: ```json { "method": "initialize", "params": {} } ```` List tools: ```json { "method": "tools/list" } ``` Call a tool: ```json { "method": "tools/call", "params": { "name": "get_subreddit_info", "arguments": { "subreddit": "technology" } } } ``` #### Legacy Format ```json { "tool": "get_subreddit_info", "params": { "subreddit": "technology" } } ``` ### Installation ```bash npm install ``` ### Testing ```bash echo '{"tool": "get_subreddit_info", "params": {"subreddit": "technology"}}' | INPUT_STORE=1 apify run ``` ### Build ```bash npm install node --check src/main.js apify push ``` ### License MIT # Actor input Schema ## `subreddit` (type: `string`): Subreddit name (without r/) ## `tool` (type: `string`): MCP tool to call: get\_subreddit\_info, get\_posts, get\_comments, search\_reddit ## `sort` (type: `string`): Sort order for posts: hot, new, top, rising ## `limit` (type: `integer`): Max number of results (1-100) ## `query` (type: `string`): Search query (for search\_reddit tool) ## Actor input object example ```json { "subreddit": "", "tool": "get_subreddit_info", "sort": "hot", "limit": 25, "query": "" } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "subreddit": "", "tool": "get_subreddit_info", "sort": "hot", "limit": 25, "query": "" }; // Run the Actor and wait for it to finish const run = await client.actor("red.cars/reddit-scraper-mcp").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "subreddit": "", "tool": "get_subreddit_info", "sort": "hot", "limit": 25, "query": "", } # Run the Actor and wait for it to finish run = client.actor("red.cars/reddit-scraper-mcp").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 '{ "subreddit": "", "tool": "get_subreddit_info", "sort": "hot", "limit": 25, "query": "" }' | apify call red.cars/reddit-scraper-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=red.cars/reddit-scraper-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Scraper MCP", "description": "Reddit MCP for AI agents. Programmatic access to subreddit info, posts, comments, and search. Built for sentiment analysis, community intelligence, and market research.", "version": "1.0", "x-build-id": "r6xi6fYALsB3NKB9a" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/red.cars~reddit-scraper-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-red.cars-reddit-scraper-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/red.cars~reddit-scraper-mcp/runs": { "post": { "operationId": "runs-sync-red.cars-reddit-scraper-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/red.cars~reddit-scraper-mcp/run-sync": { "post": { "operationId": "run-sync-red.cars-reddit-scraper-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "tool" ], "properties": { "subreddit": { "title": "Subreddit", "type": "string", "description": "Subreddit name (without r/)", "default": "" }, "tool": { "title": "Tool", "type": "string", "description": "MCP tool to call: get_subreddit_info, get_posts, get_comments, search_reddit", "default": "get_subreddit_info" }, "sort": { "title": "Sort", "type": "string", "description": "Sort order for posts: hot, new, top, rising", "default": "hot" }, "limit": { "title": "Limit", "type": "integer", "description": "Max number of results (1-100)", "default": 25 }, "query": { "title": "Query", "type": "string", "description": "Search query (for search_reddit tool)", "default": "" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```