This article provides a complete, practical walkthrough of the Schedule Slack Automation 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 Daily Meeting Summaries with n8n, Google Calendar, and Gemini AI  
   
   Meta Description:  
   Learn how to automate daily meeting summaries using n8n, Google Calendar, and Google’s Gemini AI. Save time and streamline communication by sending AI-generated summaries directly to your Slack channel each morning.
   
   Keywords:  
   n8n automation, daily summary, Gemini AI, Google Calendar integration, Slack automation, meeting recap, calendar agent, workflow automation, AI meeting assistant, Google Gemini API
   
   Third-Party APIs Used:
   
   - Google Calendar API (via n8n Google Calendar node)
   - Google Gemini API (models/gemini-1.5-flash-latest via PaLM)
   - Slack API (via n8n Slack node)
   
   —
   
   Article:  
   
   📅 Automate Meeting Summaries Using n8n, Google Calendar, and Gemini AI  
   
   In today’s fast-paced work environment, keeping up with daily meetings and communicating outcomes efficiently is crucial. However, manually summarizing meetings and sharing updates can take up valuable time. Wouldn’t it be great if this task could be taken off your plate and handled by an AI agent instead? That’s exactly what this n8n workflow is designed to do.
   
   In this article, we break down a pre-built automation that combines n8n, Google Calendar, Gemini AI, and Slack to deliver daily meeting summaries — neatly composed and shared to your team’s Slack channel each morning.
   
   🚀 Overview  
   
   The n8n workflow titled "Daily meetings summarization with Gemini AI" is designed to:
   
   - Trigger automatically every morning at 9 AM,
   - Access a user’s Google Calendar to fetch that day’s scheduled events,
   - Summarize all meetings using Google’s Gemini 1.5 Flash AI model, and
   - Send the summary directly to a designated Slack channel.
   
   The result? A smart assistant that does the daily reporting for you, keeping your team informed — no manual typing required.
   
   🛠️ How the Workflow Works  
   
   Let’s break down the components used and how they’re connected:
   
   ⏰ 1. Schedule Trigger  
   The workflow starts with a "Schedule Trigger" node configured to run daily at 9 AM. This initiates the chain of events to retrieve and summarize the day’s meetings.
   
   🤖 2. Calendar AI Agent  
   The trigger activates a calendar-specific AI agent built using the Langchain integration in n8n. This agent is given the instruction:
   
   “summarize today's meetings. startdate = YYYY-MM-DD 00:00:00, enddate = YYYY-MM-DD 23:59:59”
   
   It uses the current date to filter events and produces a context-aware prompt for the Gemini AI.
   
   📆 3. Google Calendar Integration  
   Through the Google Calendar node, the workflow fetches all events for the day from the calendar associated with john@iKemo.io. The time range is dynamically set using templated expressions based on that day’s midnight and 11:59 PM timestamps.
   
   The AI agent uses this data as input for the summary generation process.
   
   🤖 4. Google Gemini AI Model  
   A chat model node — specifically Gemini 1.5 Flash, Google’s high-speed language model — processes the prompt generated by the calendar agent. The model is primed with a system message that ensures accuracy and format consistency. It includes:
   
   - Clear date and time ranges
   - Reminder of the assistant’s duties
   - General formatting rules
   
   Once processed, Gemini returns a neat, human-like meeting summary.
   
   💬 5. Slack Integration  
   Lastly, the output is piped into a Slack node. The AI results — stripped of excess markdown — are sent to the Slack channel named #ai-chat-gemini, enabling real-time updates to collaborative teams throughout the day.
   
   🧩 Intelligent Workflow Without Memory Dependency  
   
   One noteworthy aspect of the workflow is its intentional omission of memory storage for the AI model. Since each execution is a standalone task with no need for a follow-up or contextual relevance from a previous day, a memoryless configuration ensures efficiency while staying lightweight.
   
   📊 What Makes This Workflow Effective?  
   
   - Fully automated from trigger to delivery
   - Context-aware summarization powered by Gemini 1.5 Flash
   - Seamless integration across calendar and chat platforms
   - Reduces communication overhead and human error
   - Easily customizable for other users, departments, or time zones
   
   🔌 Tools and APIs Used  
   
   This workflow is powered by the integration of powerful third-party APIs:
   
   - Google Calendar API: Accesses and retrieves meeting data.
   - Google Gemini API: Summarizes meeting data using the Gemini 1.5 Flash model.
   - Slack API: Delivers meeting recaps directly to your chosen Slack channel.
   
   🏁 Final Thoughts  
   
   With the rise of AI-assisted productivity tools, this n8n workflow showcases just how easily everyday routines can be automated. Whether you're a team leader, project manager, or remote worker, you now have a scalable method for converting calendar clutter into concise communication — every single day, without lifting a finger.
   
   This type of automation demonstrates the intelligent interconnectivity between tools like Slack, Google Calendar, and the next generation of AI models such as Gemini. It’s a modern productivity boost — built for the AI era.
   
   📣 Ready to Deploy?  
   
   To implement this workflow in your own workspace, all that’s needed is:
   
   - An n8n account and hosted environment (or local setup)
   - Connected credentials for Google Calendar, Gemini API access, and Slack
   - A valid Slack channel to post updates
   
   Once configured, sit back and let your AI assistant handle the daily summaries — so you can focus on what truly matters.
   
   —  
   By embracing automation, you not only improve efficiency but enhance your team's communication culture. Start building smarter workflows today.

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.