n8n LinkedIn Post Automation: Tavily + Ollama + Telegram

Automate technical LinkedIn posts—search with Tavily, write with Ollama, and deliver to Telegram

This n8n workflow builds a complete n8n LinkedIn Post Automation pipeline: it searches the web using Tavily for a chosen technical topic, analyzes results with an Ollama LLM, generates a 150–250 word HTML-formatted LinkedIn post with reference links, and sends the finished rich message to Telegram.

What this workflow does

• Manual start: You manually execute the workflow when you want a new post.
• Define topic + limits: Set the target topic and the maximum number of articles to fetch.
• Search with Tavily: The workflow queries the Tavily Search API, then extracts each result’s title and content snippets.
• Choose an angle with Ollama: An Ollama chat model reviews the gathered snippets and selects an interesting, technically meaningful perspective.
• Draft the LinkedIn post: A second Ollama-powered agent writes a 150–250 word technical post with one practical takeaway and relevant reference links.
• Convert to HTML + send to Telegram: The output is converted into HTML (wrapped in a simple HTML template) and delivered as a rich message to your Telegram chat.

Use cases

• SaaS operators who want consistent, technically accurate LinkedIn updates without manual research.
• Automation engineers creating content on frameworks, APIs, and engineering practices using fresh web references.
• Teams who prefer “search → analyze → write → share” in one repeatable n8n workflow.

Technical details

• Integrations: Tavily Search API (add your Tavily API key in the HTTP request Authorization header), Ollama (ensure model gpt-oss:20b is available), and Telegram (bot credentials + chat ID).
• Nodes/tools: set, html, markdown, telegram, aggregate, sticky note.

Customization: Update the topic/maxArticles values and adjust the post formatting rules as needed.

Reach out for changes!