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The LinkedIn Scraper node searches LinkedIn by keyword and returns real public posts — images, videos, captions, author details, and engagement metrics — for the query you connect. Results come from the public LinkedIn post search. Runs are repeatable: the node maps your query and settings directly to a keyword search instead of improvising one.

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When to use

  • B2B content research — see what professionals are posting on a topic
  • Thought leadership trends — track content formats and messaging in your industry
  • Competitive intelligence — monitor public content from companies and individuals
Common pattern: text_prompt → linkedin_scraper.

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Inputs

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Query
text
required
The keyword or phrase to search on LinkedIn. Required.

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Outputs

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Results
any
Everything the scrape produced — post records, images, videos, and the summary — as one connectable output. Connect it to an AI node’s Context input to analyse or rewrite the content.

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Referencing results in prompts

Connect Results to a Generate Text node’s Context input. Each item gets a stable name you can use in your prompt — [post_1], [image_2], [text_1] — e.g. “Rewrite the caption of post_2 for our brand voice; ignore the rest.”

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Configuration

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Max Results
number
default:"10"
Maximum number of posts to return. Range: 1–50.
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Period
string
default:"Last 30 days"
Time window for results: Last 24 hours, Last 7 days, Last 30 days, or All time.

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Analysis (optional)

Leave blank to get the default count summary at no extra cost.
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Analysis Prompt
string
Custom instructions for the AI model. When set, the model reads all fetched posts and writes a summary following your instructions (e.g. “Identify common messaging angles and content formats”). Adds 1 credit per run.
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Analysis Model
string
default:"Gemini 2.5 Flash"
The AI model used to generate the analysis. Only applies when Analysis Prompt is set.
Results come from public LinkedIn posts and reflect publicly available content. This node costs 1 credit per run, plus 1 additional credit when AI analysis is enabled.