Data collection bottlenecks
Traditional crawlers face anti-climbing mechanisms, and manual collection cannot meet the needs of large-scale projects.
integrated solution
- process automation::
- Write shell scripts to loop through keyword files
- Sample code:
while read kw; do npx g-search-mcp --keywords "$kw" > output_${kw}.json; done < keywords.txt
- data enhancement::
- combining
--localeParameters to get multilingual results - utilization
--limit 50Expanding the sample size
- combining
- Results processing::
- Parsing data with the Python json module
- Recommended pandas to do result de-duplication and analysis
Extended Recommendations
Advanced Usage:
- Setting up timed tasks (cron or Windows Task Plan)
- Integration into the Scrapy framework as a complementary data source
- Secondary crawling using the URLs in the results
This answer comes from the articleG-Search-MCP: MCP Server for Free Google SearchThe
May not be reproduced without permission:AI productivity tools " How to apply G-Search-MCP for automated information collection in data mining projects?
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