This article provides a complete, practical walkthrough of the Schedule Http Create Scheduled n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   Automated Financial News Digest with n8n and AI: Boost Your Market Insight Daily
   
   Meta Description:
   Discover how an n8n workflow automatically curates financial news from FT.com and delivers personalized AI-generated summaries every morning via email—designed to empower investors with actionable insights.
   
   Keywords:
   n8n workflow, financial news automation, AI news summarization, Google Gemini, Microsoft Outlook, FT.com, market insights, HTML parsing, investor newsletter, PaLM API, automated news digest
   
   Article:
   
   Stay Ahead of the Financial Curve: An Automated News Digest Using n8n and AI
   
   In the rapidly evolving financial world, timely and relevant information is essential for informed decision-making. With investors juggling multiple information channels, the ability to consolidate and summarize key market updates has become a crucial productivity tool. Thanks to a powerful automated workflow built with n8n, you can now receive a consolidated, AI-summarized financial news digest in your inbox every morning at 7:00 AM—without lifting a finger.
   
   This article outlines a smart automation solution that fetches financial news from FT.com (The Financial Times), parses meaningful content, summarizes it with the help of Google Gemini (PaLM model), and sends it via Microsoft Outlook in a clean, well-structured HTML format.  
   
   Let’s dive into how this works and what makes this automation not only functional but also indispensable.
   
   ⏰ Step 1: Scheduled Automation Trigger
   
   The journey starts with an n8n Schedule Trigger node. The workflow is set to run every day at 7:00 AM sharp—ideal timing for early risers or pre-market strategists. This ensures that the latest headlines and insights are waiting in your inbox as you start your day.
   
   🌐 Step 2: Fetching Financial News Articles
   
   Once triggered, the workflow performs an HTTP request to https://www.ft.com/ using the Get Financial News Online node. The FT is a globally respected source of financial journalism, ensuring the content retrieved is both credible and insightful.
   
   📰 Step 3: HTML Parsing and Content Extraction
   
   Probably the most intricate part of this workflow, the Extract Specific Content node utilizes CSS selectors to scrape targeted information from the FT.com homepage. The configured selectors hunt down:
   
   - Headline #1 and Headline #2  
   - Editor's Picks  
   - Top Stories  
   - Spotlight Features  
   - Various News Segments  
   - Europe-Centric News  
   
   The node uses precise CSS selectors to isolate critical sections of the HTML DOM, stripping away unnecessary clutter like headers (via skipSelectors), and cleaning up the text for easy reading.
   
   📦 Step 4: Aggregating the News Elements
   
   In the Gather the Elements step, all retrieved data is elegantly compiled into a single string. Each category of content is grouped and labeled to aid further processing. This structure sets up a clear context for the AI agent to interpret and summarize.
   
   🤖 Step 5: AI-Powered Summarization with Google Gemini
   
   Here’s where things get intelligent. The AI Agent node is powered by Google's Gemini language model (part of the PaLM API family), which receives the aggregated content and processes it through a defined system prompt:
   
   "You are to summarize today's financial news. The summary will help an investor to have a clear view of the market and make better decisions. Write the body of an email using a well-structured HTML format."
   
   The AI prepares a cohesive, insightful summary formatted for email, designed specifically to assist investors with actionable knowledge.
   
   📧 Step 6: Automated Email Delivery via Microsoft Outlook
   
   Lastly, the Send the Summary by E-mail node steps in. Using Microsoft Outlook’s API, the workflow sends out the AI-crafted summary with the subject line “Financial news from today.” With HTML formatting enabled, the email is clean, structured, and effortlessly readable on any device.
   
   This makes the final output not just informative, but also visually appealing and highly professional—perfect for sharing within teams or decision-makers on the go.
   
   🎯 The Impact: Data-Driven Decisions at Dawn
   
   By combining scraping, content aggregation, AI summarization, and direct email delivery, this workflow transforms raw, unstructured web content into a daily advisory asset for financial professionals and retail investors alike.
   
   Whether you're keeping tabs on macroeconomic shifts, sector movements, or regional developments in Europe, this workflow ensures that nothing important slips through the cracks—saving you hours of manual research and digestion.
   
   ✅ Key Benefits:
   
   - Saves time by automating content extraction and communication
   - Uses trusted sources (FT.com) for accuracy and relevance
   - Personalized insights generated by Google Gemini (PaLM) AI
   - Ready-to-read email format for instant actionability
   - Can be extended to include more sources (like Yahoo Finance)
   
   🔌 Third-Party APIs and Services Used
   
   1. Google Gemini Chat Model (PaLM via LangChain integration)
      - Purpose: Summarize financial news in email-ready HTML format
      - Credential Node: googlePalmApi
   
   2. Microsoft Outlook API
      - Purpose: Automatically email the generated summary
      - Credential Node: microsoftOutlookOAuth2Api
   
   3. FT.com (https://www.ft.com/)
      - Source: Structured HTML content is scraped for financial headlines and analysis
   
   🔄 Final Thoughts
   
   This n8n-powered workflow is a stellar example of how automation, AI, and good design can reinvent how we consume financial information. By delivering a summarized morning brief every day, it frees up valuable time and enhances strategic decision-making—all with the reliability of scheduled execution and the intelligence of modern AI.
   
   For companies, individual investors, or financial advisors, this automation could serve as the foundation for a personalized market intelligence tool that scales.
   
   Try implementing it today and usher in a smarter way to start your financial journey—one email at a time.
   
   Stay informed. Stay empowered.
   
   —  
   Written by your friendly AI assistant helping you automate smarter with n8n.
   
   Let me know if you’d like this workflow as a downloadable .json file or hosted in a public GitHub repository.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.