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io.github.johnisanerd/linkedin-posts

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by johnisanerd Β· Python

Scrape and analyze public LinkedIn posts as structured JSON via the Apify LinkedIn Posts API.

Model Context Protocol (MCP) Server: io.github.johnisanerd/linkedin-posts

This MCP server scrapes and analyzes public LinkedIn posts, returning results as structured JSON via the Apify LinkedIn Posts API. It can discover a person’s recent posts from a public LinkedIn profile URL or fetch specific posts by passing post URLs, producing one JSON row per post.

πŸ› οΈ Key Features

  • Uses the Apify LinkedIn Posts API for scraping and analysis
  • Accepts a public LinkedIn profile URL to discover recent posts
  • Accepts specific post URLs to fetch posts directly
  • Returns structured JSON per post including text, reactions, and comments

πŸš€ Use Cases

  • Extract and analyze public LinkedIn post content
  • Collect engagement signals (reactions and comments) for posts
  • Drive content-research workflows from LinkedIn URLs

⚑ Developer Benefits

  • Structured JSON output: one clean JSON row per post
  • Fields surfaced per post: text, reactions, comments
  • Designed for API-based consumption in developer workflows

⚠️ Limitations

  • Focuses on public LinkedIn posts
  • Does not describe authenticated/private post access in provided data

Topics

api, apify, content-research, engagement, linkedin, linkedin-posts, mcp, python, social-media

Topics

apiapifycontent-researchengagementlinkedinlinkedin-postsmcppythonsocial-media

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