Build an AI-Powered Research Assistant with Linear + Scrapeless
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Automate your research directly from Linear! This n8n workflow transforms Linear issues into a powerful command center for web data. Trigger advanced searches, trend analysis, and web scraping tasks with simple commands, saving hours on manual data collection.
About This Workflow
This n8n workflow empowers you to conduct comprehensive web research effortlessly, using Linear as your command interface. By simply creating a new Linear issue with specific commands like /search, /trends, /scrape, or /crawl in its title, you can automatically initiate a range of data gathering operations via Scrapeless. From performing targeted Google searches and monitoring trending topics to unlocking complex web pages and deep crawling sites, this workflow streamlines your research process. The collected data is then ready for further analysis, making it a perfect foundation for building an AI-powered assistant (e.g., by connecting to a tool like Claude for summarization or insight extraction).
Key Features
- Linear-Driven Commands: Initiate diverse research tasks by adding specific commands (e.g.,
/search,/trends,/scrape) to Linear issue titles. - Multi-faceted Web Data Collection: Access Google Search results, Google Trends data, perform targeted web scraping, or full site crawls using Scrapeless.
- Advanced Web Unlocking: Utilize Scrapeless's web unlocker to bypass bot detection and access content from challenging websites.
- Automated Research: Drastically reduce manual effort in data gathering for market analysis, competitor insights, or content generation.
- Extensible for AI: Provides structured data output, ideal for integration with Large Language Models (LLMs) for AI-powered summarization and analysis.
How To Use
- Configure Linear Trigger: Connect your Linear account and select the team(s) and resources (issues, comments, reactions) you want to monitor.
- Set up Scrapeless Credentials: Ensure your Scrapeless API key is securely configured in n8n for all Scrapeless nodes.
- Understand Command Structure: To trigger specific actions, create a Linear issue with a command (e.g.,
/search your query,/trends topic,/unlock URL,/scrape URL,/crawl URL) in its title. - Customize Data Processing: Review the "Code" nodes to understand how they clean the commands from the Linear issue titles, and customize if necessary.
- Integrate AI (Optional but Recommended): Extend the workflow by adding a Large Language Model (e.g., Claude, OpenAI) node after the Scrapeless outputs to process, summarize, or analyze the gathered data.
- Activate and Test: Enable the workflow and test by creating issues in Linear with your desired commands.
Apps Used
Workflow JSON
{
"id": "ecda8433-c87c-4297-b301-f98b3adfc09a",
"name": "Build an AI-Powered Research Assistant with Linear + Scrapeless",
"nodes": 25,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: ecda8433-c87c...
About the Author
AI_Workflow_Bot
LLM Specialist
Building complex chains with OpenAI, Claude, and LangChain.
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