This article provides a complete, practical walkthrough of the Googletaskstool Telegram Automation Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Advanced setup in 1-2 hours. One‑time purchase: €69.

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:  
   Automating Clinical Operations with AI Agents in n8n: A Deep Dive into the “Agente” Workflow
   
   Meta Description:  
   Discover how this sophisticated n8n workflow leverages AI agents, Google services, and messaging APIs to automate appointment scheduling, rescheduling, shopping lists, and patient interactions in a clinical setting.
   
   Keywords:  
   n8n workflow, AI assistant, clinical automation, OpenAI GPT-4, Google Calendar API, appointment rescheduling, WhatsApp integration, Telegram bot, Evolution API, healthcare automation, LangChain agents, Google Tasks, AI in clinics, conversational AI, appointment confirmation
   
   Third-Party APIs and Tools Used:
   
   1. OpenAI API (GPT-4 & Whisper transcription)
   2. OpenRouter API (Gemini models for advanced reasoning)
   3. Google Calendar API (via MCP CALENDAR tool)
   4. Google Tasks API
   5. Telegram Bot API
   6. Evolution API (WhatsApp messaging and media processing)
   7. PostgreSQL (for maintaining AI memory context)
   
   Article:
   
   Empowering Clinical Efficiency with AI Workflow Automation Using n8n
   
   In the evolving landscape of healthcare, automation is no longer a luxury — it is a necessity. The “Agente” workflow built in n8n represents a perfect blend of modern AI-driven architecture and pragmatic clinic operations. Designed to support a real-world clinical environment, this system tackles everything from daily appointment confirmations to dynamic rescheduling and shopping list management.
   
   Let’s unwrap the critical components that bring this intelligent assistant to life.
   
   Central Objective: Streamlined Patient Support
   
   The "Agente" workflow operates primarily as a digital assistant, aimed at helping clinic professionals with:
   
   - Reagendamento de consultas (Appointment Rescheduling)  
   - Confirmação de consultas (Appointment Confirmation)  
   - Interações com pacientes via WhatsApp  
   - Inclusão de lembretes na lista de compras da clínica (Clinic Shopping Reminders)  
   
   This is all triggered seamlessly through channels like Telegram and WhatsApp with built-in logic ensuring no step is left behind.
   
   AI Agents, Defined Roles & Natural Language Intelligence
   
   At the heart of the system lies a set of LangChain agents powered by GPT-4 and Gemini (via OpenAI and OpenRouter). These agents exhibit distinct personalities and roles:
   
   - Assistente Clínica: Handles general patient interactions via WhatsApp, including appointment scheduling and cancellations.
   - Assistente Clínica Interno: Acts as an internal coordinator, triggered via Telegram by clinic staff to manage reschedules and shopping items.
   - Assistente de Confirmação: Automatically triggers every weekday at 8 AM to check next-day appointments and sends confirmation messages to patients.
   
   These agents use clearly defined system prompts to understand their boundaries, interact empathetically, and maintain compliance with clinical protocols. Contextual continuity is managed using Postgres Chat Memory, ensuring AI interactions remain coherent across sessions.
   
   Calendars, Tasks, and Complex Interactions
   
   Managing appointments at scale requires robust handling of Google Calendar data. This is achieved through the MCP (Medical Calendar Protocol) tools that provide functions such as:
   
   - GET_CALENDAR / GET_ALL_CALENDAR: Retrieve event details.
   - CREATE / UPDATE / DELETE_CALENDAR: Manage event lifecycle.
   - AVALIABILITY_CALENDAR: Check real-time availability between time windows.
   
   Agents also interact with Google Tasks for managing to-do items — specifically for inserting clinic shopping reminders upon request.
   
   Furthermore, agents have built-in escalation rules. For instance, if a patient complains, requests medical opinion, or reports urgent symptoms, the system smartly routes the message to a human attendant via the CallToHuman tool.
   
   WhatsApp + Telegram: Conversational Interfaces
   
   The system integrates WhatsApp via the Evolution API, enabling rich interactions including text, audio, media, and document handling. Audio messages are converted into MP4, transcribed through OpenAI’s Whisper model, and then processed by conversation agents.
   
   Telegram acts as the input channel for clinic staff, triggering tasks such as reschedules and list additions. Once a directive is issued, the assistant gathers data, consults the calendar, and executes backend operations transparently. All outputs are relayed back to Telegram confirmations, closing the loop cleanly.
   
   Image Analysis and Future Extensions
   
   The system is even capable of handling images through OpenAI Vision. If a patient sends images with prescriptions or handwritten notes, the model reads and describes their content via OCR and AI commentary, aiding in context-building for future replies.
   
   Clean message formatting is achieved through a dedicated AI Agent that translates markdown-like syntax into WhatsApp-compliant formatting (e.g., converting **bold** to *bold*). This ensures linguistic professionalism across all outputs.
   
   Scheduled Automation: Daily Hygiene Routine
   
   A daily “Gatilho diário” (Scheduled Trigger) ensures all patients with next-day appointments are contacted for confirmation. This reduces last-minute cancellations and increases operational predictability. It taps into Google Calendar, fetches event metadata, retrieves contact info, and sends reminders using WhatsApp — all fully automated.
   
   Takeaway: A Blueprint for Clinical 2.0
   
   The “Agente” n8n workflow is much more than a chatbot or calendar script. It represents the growing confluence of LLM-powered logic, real-time data APIs, rich messaging platforms, and distributed task automation. It enables clinics to offload repetitive administrative tasks while maintaining a warm, human-like communication style.
   
   With tools like n8n, APIs like Evolution and OpenAI, and platforms like Telegram and Google Workspace stitched together, healthcare practitioners now have a reliable digital ally — precise, polite, and perpetually available.
   
   This is what clinic automation looks like when AI is choreographed with care.
   
   — End of Article —

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.