WeChat Article Search Scraper finds public WeChat articles using configurable search and date inputs, opens matching article pages, and returns full article records without requiring account-only access.
What Does BrowserAct WeChat Article Search Scraper Do?
This BrowserAct template runs a validated, reusable extraction path against publicly accessible pages. Configure the inputs, run the Bot, and receive structured records without writing selectors or browser scripts.
Key Features
- Search public articles with reusable keyword and publication-date inputs.
- Open matching public article detail pages.
- Extract titles, body content, images, authors, dates, and source links.
- Stop at the requested count or when no more matching public results remain.
- Return optional image fields as empty when unavailable.
What Data Can I Extract from WeChat Articles?
| Field | Description |
|---|---|
title |
Public article title. |
body_content |
Readable article body text. |
image_url |
Article image URL when available. |
author |
Article author or account name. |
publication_date |
Visible publication date. |
url_link |
Public article URL. |
How to Use WeChat Article Search Scraper
- Click Run task.
- Enter the configurable values shown below.
- Run the Bot and review the structured records.
- Export the result or connect it to an API, automation platform, or agent workflow.
Input Parameters
| Parameter | Required | Default | Description |
|---|---|---|---|
Keywords |
Yes | openclaw |
Terms used to find public WeChat articles. |
Publication Date |
No | 2026-03-11 |
Date filter used by the public search flow. |
Count |
Yes | 5 |
Maximum article records to return. |
Example Output
{
"results": [
{
"title": "Example WeChat article",
"body_content": "Full readable article content...",
"image_url": "https://example.com/article-image.jpg",
"author": "Example Publisher",
"publication_date": "2026-03-11",
"url_link": "https://mp.weixin.qq.com/s/example"
}
]
}
How Does it Work?
BrowserAct applies the configured keywords and publication date to the public article discovery flow, then reads the available matching results.
The Bot opens each public article detail page, captures the visible article fields, preserves the article URL, and continues until Count is reached. The successful default run returned five article records.
How to Build a New Scraper Bot with Agent Built
Step 1: Describe the Data You Need
Open BrowserAct and start Agent Built from the Home prompt box or from Create -> Build with Agent. Paste a clear request that includes the website, the records to collect, the filters or search conditions, the fields to return, the result limit, and the inputs you want to reuse later.
Step 2: Let BrowserAct Build and Test the Bot
BrowserAct explores the live website, works out the navigation and extraction path, and validates the result. If BrowserAct asks for clarification, reply in the same build conversation with the missing URL, condition, field, example, or expected output.
Step 3: Run the Bot and Review the Result
When the build is complete, run the Bot with the default inputs first. Review the structured records, source URLs, missing fields, and row count before reusing the Bot with new inputs or connecting it to another workflow.
Why Use WeChat Article Search Scraper?
Collect public WeChat articles for media monitoring, topic research, source review, and structured content analysis.
Who Can Use This Template?
- Media monitoring teams.
- Content researchers.
- Brand and market analysts.
- Automation builders organizing public article datasets.
How Many Results Can You Scrape?
Count controls the maximum article records. Actual availability depends on public search access, date coverage, and matching results.
Automation and Export
BrowserAct returns structured data first. You can then use the completed output through API JSON responses, n8n workflows, Make scenarios, Zapier automations, MCP-based agent workflows, or manual CSV and spreadsheet review.
Need Help?
Contact us at
Discord: Discord Community
E-mail: service@browseract.com
