# WeChat Video Downloader & Scraper (`fastcrawler/wechat-video-downloader-scraper`) Actor Easily extract and download high-quality WeChat videos. This actor retrieves direct video URLs, cover images, and post metadata, returning clean, structured data (JSON/CSV) ready for seamless API integration and automated workflows. - **URL**: https://apify.com/fastcrawler/wechat-video-downloader-scraper.md - **Developed by:** [fastcrawler](https://apify.com/fastcrawler) (community) - **Categories:** AI, Agents, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 wechatresults 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/platform/actors/running/actors-in-store#pay-per-event ## 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ### WeChat Video Downloader & Scraper | 2026 Easily extract and download high-quality WeChat videos and their associated metadata—instantly and accurately. This actor takes WeChat video URLs as input and retrieves direct video links (both H.264 and H.265 formats), cover images, engagement statistics, and author information. It is designed to be highly reliable and developer-friendly, making it the perfect choice for content creators, researchers, and automated data pipelines. #### 🌟 Key Features: - 📥 **Direct Video Links**: Extract direct download URLs for H.264 and H.265 video formats. - 📊 **Rich Metadata**: Retrieve engagement metrics including likes, favorites, forwards, and comment counts. - 👤 **Author Details**: Get the creator's nickname and profile image. - ⚡ **High-Speed & Reliable**: Built for fast execution and consistent data extraction. - 🛠️ **Developer Ready**: Output clean, structured JSON/CSV data ready for seamless API integration and downstream processing. #### 📥 Input The actor accepts a list of WeChat video URLs. *Example:* `https://weixin.qq.com/sph/AJLFSHpwqI` #### 📤 Output Example The extracted data is flattened and structured for easy export to CSV, JSON, or Excel. Here is a sample of the output you can expect: { "nickname": "雨哥努力日记", "description": "这是一款可以让你白嫖全网视频的开源项目...", "h264VideoUrl": "https://finder.video.qq.com/...", "h265VideoUrl": "https://finder.video.qq.com/...", "createtime": 1782626401, "favCountFmt": "489", "likeCountFmt": "138", "forwardCountFmt": "3395", "commentCountFmt": "26", "coverUrl": "https://finder.video.qq.com/..." } --- ### Contact and Feature Requests If you need customized features, bulk processing capabilities, or have specific requirements for your automated workflows, feel free to contact me: 📩 **Email:** fastcrawler9@gmail.com 💬 **[Telegram](https://t.me/+MUMR3PKOoVVjNzE9)** 🧑‍🤝‍🧑 **[Discord](https://discord.gg/s4jyupzaWu)** # Actor input Schema ## `video_url_list` (type: `array`): Enter the WeChat video URLs you want to process. You can provide up to 10 URLs. ## Actor input object example ```json { "video_url_list": [ "elonmusk", "axiaisacat" ] } ```` # Actor output Schema ## `overview` (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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "video_url_list": [ "elonmusk", "axiaisacat" ] }; // Run the Actor and wait for it to finish const run = await client.actor("fastcrawler/wechat-video-downloader-scraper").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 = { "video_url_list": [ "elonmusk", "axiaisacat", ] } # Run the Actor and wait for it to finish run = client.actor("fastcrawler/wechat-video-downloader-scraper").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 '{ "video_url_list": [ "elonmusk", "axiaisacat" ] }' | apify call fastcrawler/wechat-video-downloader-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fastcrawler/wechat-video-downloader-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "WeChat Video Downloader & Scraper", "description": "Easily extract and download high-quality WeChat videos. This actor retrieves direct video URLs, cover images, and post metadata, returning clean, structured data (JSON/CSV) ready for seamless API integration and automated workflows.", "version": "0.0", "x-build-id": "N6ZC84ru25K6gfvfA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fastcrawler~wechat-video-downloader-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fastcrawler-wechat-video-downloader-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fastcrawler~wechat-video-downloader-scraper/runs": { "post": { "operationId": "runs-sync-fastcrawler-wechat-video-downloader-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fastcrawler~wechat-video-downloader-scraper/run-sync": { "post": { "operationId": "run-sync-fastcrawler-wechat-video-downloader-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "video_url_list" ], "properties": { "video_url_list": { "title": "video_url_list (Up to 10 items)", "type": "array", "description": "Enter the WeChat video URLs you want to process. You can provide up to 10 URLs.", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```