apify
Use when scraping websites, extracting structured data from listing sites, running prebuilt scrapers/actors, or automating stubborn web research workflows. Make sure to use this whenever apartment hunting, marketplace scraping, anti-bot-resistant extraction, or batch website data collection would benefit from a dedicated scraping platform rather than ad hoc browser clicks.
What this skill does
# Apify
Use Apify as the heavy-duty scraping and extraction layer.
It is especially useful when:
- a site is JS-heavy or anti-bot-prone
- we need many listings, not just one page
- a community Actor already exists for the target site
- we want structured output instead of manual copy/paste from the browser
## Best use cases
- Apartment / real-estate site scraping
- Airbnb / booking / marketplace extraction
- Bulk listing collection across multiple sites
- Converting messy listing pages into structured datasets
## MCP usage
Call via:
```python
skill_mcp(mcp_name="apify", tool_name="...", arguments={...})
```
## Recommended flow
1. Search for a relevant Actor.
2. Inspect the Actor details and inputs.
3. Run the Actor.
4. Read the dataset items.
5. Normalize results into a shortlist.
## Typical tools
### Search for a scraper
```python
skill_mcp(mcp_name="apify", tool_name="search-actors", arguments={"query": "airbnb scraper"})
```
### Use the built-in web extraction path
```python
skill_mcp(mcp_name="apify", tool_name="apify/rag-web-browser", arguments={"url": "https://example.com/listing"})
```
### Run a chosen Actor
```python
skill_mcp(mcp_name="apify", tool_name="call-actor", arguments={
"actorId": "apify/example-actor",
"input": {"startUrls": [{"url": "https://example.com"}]}
})
```
### Read results
```python
skill_mcp(mcp_name="apify", tool_name="get-dataset-items", arguments={"datasetId": "DATASET_ID"})
```
## Notes
- Requires `APIFY_TOKEN` in the environment.
- Apify is best when we need scale, repeatability, or structured output.
- Prefer Apify over fragile one-off browser scraping when the task looks repeatable.
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