Research Scenario Requirements
Academic research often needs to compare multiple related concepts (e.g., "neural network, deep learning, reinforcement learning"), and traditional one-by-one searches are time-consuming and difficult to integrate data.
Technology realization programme
- Parallel search mechanism: Separate keywords with commas (
--keywords "A,B,C") Automatically turn on multi-tab synchronized queries - Structured Output: JSON format contains the original query words and the corresponding results, which is convenient for subsequent analysis.
- Customized results: By
--limitParameters control the number of entries returned for each keyword (20-50 entries recommended to balance quality)
Efficiency Improvement Tips
Recommended Workflow:
- Save key phrases as a text file for batch recall via shell scripts
- The result is redirected to the file:
> research_data.json - Use the jq tool to extract specific fields:
jq '.searches[].results[].title' research_data.json
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 optimize the efficiency of multi-keyword searches to improve the speed of research information collection?
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