Wikipedia Search Results Scraper is a BrowserAct Bot template for collecting structured records from public Wikipedia full-text search results. Configure a Wikipedia base URL, keyword, and result count, then run the Bot to return ranked page records for research, content planning, SEO analysis, knowledge-base enrichment, or automation workflows.
What Does BrowserAct Wikipedia Search Results Scraper Do?
This template opens a Wikipedia full-text search page, extracts the main result list, follows pagination when needed, and returns one structured record per Wikipedia page result.
Key Features
- Extract public Wikipedia search results without requiring a login.
- Capture rank, title, URL, snippet, namespace, timestamp, size, word count, and keyword.
- Configure base URL, keyword, and count.
- Continue through search result offsets until the requested count is reached.
- Exclude sister-project blocks so the output focuses on primary Wikipedia page results.
What Data Can I Extract from Wikipedia?
| Field | Description |
|---|---|
rank |
Search result position. |
title |
Wikipedia page title. |
url |
Public Wikipedia page URL. |
snippet |
Search result snippet. |
namespace |
Result namespace or page type, such as Article. |
last_updated |
Timestamp shown in the result metadata. |
size |
Page size shown in the result metadata. |
word_count |
Word count parsed from the result metadata. |
keyword |
Search keyword used for the run. |
How to Use Wikipedia Search Results Scraper
- Click Run task.
- Enter the Wikipedia base URL, such as
https://en.wikipedia.org. - Enter a keyword or topic.
- Set how many search result records to collect.
- Run the Bot and review the structured results.
- Reuse the Bot with another topic, language edition, or downstream workflow.
Input Parameters
| Parameter | Required | Default | Description |
|---|---|---|---|
base_url |
Yes | https://en.wikipedia.org |
Wikipedia site origin, such as the English Wikipedia domain. |
keyword |
Yes | artificial intelligence |
Search keyword or phrase. |
count |
Yes | 20 |
Maximum number of search result records to return. |
Example Output
The table below uses records preserved from the validated Bot run. Up to the first 5 records are shown, and long values are shortened in this documentation preview.
| rank | title | url | snippet | namespace | last_updated | size | word_count | keyword |
|---|---|---|---|---|---|---|---|---|
| 1 | Artificial intelligence | https://en.wikipedia.org/wiki/Artificial_intelligence | Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence. | Article | 17:08, 19 August 2026 | 272 KB | 27624 | artificial intelligence |
How Does it Work?
BrowserAct constructs a public Wikipedia full-text search URL from base_url and keyword, opens the result page, and extracts only the main search result items. Each result is mapped into a ranked record with title, URL, snippet, namespace, last-updated timestamp, size, word count, and keyword.
When count is higher than the first page, BrowserAct follows Wikipedia result offsets until the requested number of records is collected or no more results are available. Sister-project result blocks are ignored so the output stays focused on Wikipedia pages.
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 Scrape Wikipedia Search Results?
Wikipedia search data helps teams discover public knowledge pages, collect topic references, map related concepts, analyze encyclopedia coverage, and route structured topic records into reports, dashboards, databases, or agents.
Who Can Use This Template?
- Researchers collecting encyclopedia references.
- Content and SEO teams mapping related topics.
- Knowledge-base teams enriching internal records.
- Product teams monitoring public topic coverage.
- Automation builders routing page records into spreadsheets, databases, alerts, or agents.
How Many Results Can You Scrape?
Use count to control the number of Wikipedia result records returned. Higher counts require moving through more result offsets and may take longer depending on Wikipedia response speed.
Automation and Export
BrowserAct returns structured Wikipedia search records first. You can then use the output through API JSON responses, n8n workflows, Make scenarios, Zapier automations, MCP-based agent workflows configured from the Bot's Integrations tab, or manual CSV review.
Need Help?
Contact us at
Discord: Discord Community
E-mail: service@browseract.com
