Homebrew Formula Search Scraper is a BrowserAct Bot template for collecting structured Homebrew formula and cask records from public Homebrew search results. Configure a keyword and result count, then run the Bot to return ranked package metadata for developer tooling, dependency research, software cataloging, DevOps workflows, or automation pipelines.
What Does BrowserAct Homebrew Formula Search Scraper Do?
This template searches Homebrew's public package site for your keyword, resolves matching formula and cask results, enriches them from public Homebrew JSON data, and returns one structured record per package.
Key Features
- Extract public Homebrew formula and cask search results without requiring a login.
- Capture rank, package name, package URL, type, install command, description, current version, install analytics, homepage, license, and search keyword.
- Configure base URL, keyword, and count.
- Use Homebrew's public search backend and public package JSON pages.
- Return records ready for package catalogs, developer tooling, dashboards, and agent workflows.
What Data Can I Extract from Homebrew?
| Field | Description |
|---|---|
rank |
Search result position assigned by the Bot. |
package_name |
Homebrew formula or cask name. |
package_url |
Public Homebrew package page URL. |
type |
Whether the result is a formula or cask. |
install_command |
Suggested Homebrew install command. |
description |
Package description from public Homebrew data. |
current_version |
Current stable version when available. |
analytics_install_count |
Public 365-day install analytics when available. |
homepage_url |
Package homepage URL. |
license |
License when available. |
search_keyword |
Keyword used for the run. |
How to Use Homebrew Formula Search Scraper
- Click Run task.
- Enter the Homebrew base URL.
- Enter a formula, app, tool, language, framework, or package keyword.
- Set how many package records to collect.
- Run the Bot and review the structured Homebrew package results.
- Reuse the Bot with another keyword or connect the output to your workflow.
Input Parameters
| Parameter | Required | Default | Description |
|---|---|---|---|
base_url |
Yes | https://formulae.brew.sh |
Public Homebrew formulae site base URL. |
keyword |
Yes | python |
Search keyword used to find matching formulae and casks. |
count |
Yes | 20 |
Maximum number of package records to return. |
Example Output
{
"results": [
{
"rank": 1,
"package_name": "python@3.14",
"package_url": "https://formulae.brew.sh/formula/python@3.14",
"type": "formula",
"install_command": "brew install python@3.14",
"description": "Interpreted, interactive, object-oriented programming language",
"current_version": "3.14.7",
"analytics_install_count": "2931266",
"homepage_url": "https://www.python.org/",
"license": "Python-2.0",
"search_keyword": "python"
}
]
}
How Does it Work?
BrowserAct uses the same public search backend that powers Homebrew's site search, because the plain {base_url}/formulae/?q={keyword} URL is not a real search results page on the Homebrew site. The Bot sends the keyword to Homebrew's public search data source, reads matching formula and cask hits, and keeps the requested rank order.
For each package hit, BrowserAct fetches the package's public Homebrew JSON data to enrich the record with description, current version, homepage, license, and install analytics. The install command is generated from the package type: formulae use brew install {name}, while casks use brew install --cask {name}.
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 Homebrew Formula Search Results?
Homebrew search data helps teams discover macOS and Linux packages, compare CLI tools and desktop apps, monitor package popularity, build internal developer-tool catalogs, and route package metadata into reports, dashboards, or agent workflows.
Who Can Use This Template?
- Developers researching CLI tools, runtimes, and macOS apps.
- DevOps teams building internal package catalogs.
- Platform teams comparing package versions and install commands.
- Developer relations teams monitoring ecosystem visibility.
- Automation builders routing package metadata into spreadsheets, databases, alerts, or agents.
How Many Results Can You Scrape?
Use count to control the number of Homebrew package records returned. Homebrew search exposes up to the first 1,000 matches for a keyword, and BrowserAct collects records until the requested count or available result limit is reached.
Automation and Export
BrowserAct returns structured Homebrew package 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

