WhatsApp assistant with Gemini AI for calendar management via Evolution API

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

AI Agent that uses MCP Server to execute actions requested via Evolution API. This workflow receives messages and media from WhatsApp via the Evolution API, converts the content into structured inp...

Best for

Support Chatbot automation workflows
AI Chatbot automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.webhook, n8n-nodes-base.switch, n8n-nodes-evolution-api.evolutionapi, @n8n/n8n-nodes-langchain.googlegemini, n8n-nodes-base.set, n8n-nodes-base.converttofile, @n8n/n8n-nodes-langchain.lmchatgooglegemini, @n8n/n8n-nodes-langchain.memorybufferwindow

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Pedro Protes.

Original n8n.io source

1.1 Workflow description

Title: WhatsApp assistant with Gemini AI for calendar management via Evolution API
Workflow name: WhatsApp assistant with Gemini AI for calendar management via Evolution API

AI Agent that uses MCP Server to execute actions requested via Evolution API.

This workflow receives messages and media from WhatsApp via the Evolution API, converts the content into structured inputs, and forwards them to an AI Agent capable of triggering MCP tools to execute external actions.

🔧 How it works

A Webhook receives messages sent to WhatsApp via the Evolution API.
The "Message Type" node detects and forwards the received media. It handles the types Text, Image, Audio, and Document. If it is another media type, the fallback forwards a "media not supported" message to the user.
The message goes to the system where it retrieves the Base64 of the media.
The media is converted into Binary File(s) and a Gemini node will generate a text input for the agent.
The AI Agent receives the structured input and calls the appropriate MCP Tool. In this example, only one MCP Server was configured.
The AI Agent generates the output and sends it to the user.

🗒️ Requirements

Evolution API Account, with the instance configured.
Gemini API.
Google Calendar API.
MCP Server (Internal or external, whichever you prefer) configured and with a URL to link to the MCP Tool.

✔️ How to set up

Configure the Evolution API webhook
- Copy the webhook URL generated in the first node.
- In the Evolution API panel, go to the instance > webhook > paste the URL into the corresponding field.
Configure Google Calendar credentials
- In n8n, go to Credentials → Create New and select Google Calendar OAuth2.
- Select this credential in all Google Calendar MCP nodes (Get, Create, Update, Delete).
Enable MCP Server nodes
- Copy the MCP Server URL and paste it into the “Endpoint field of the MCP Tool.
Configure Evolution API nodes
- In all Evolution API nodes, you need to fill in the “instance field with the name of your Evolution API instance.

🦾 how to adapt it?

Customize or extend the MCP Tools
- You can add new MCP tools (e.g., Google Sheets, Notion, ClickUp).
- Only the agent prompt needs to be updated; the workflow structure remains the same.
I opted to use simple memory, but if you want the agent to remember the entire conversation, I recommend changing the memory type; as it is, it will only remember the last 8 messages.
If you're going to use a tool like Chatwoot or TypeBot, simply change the webhook URL and pay attention to the objects that the switch (Message Type) uses.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Webhook

Type / Role: n8n-nodes-base.webhook - webhook
Config choices: Version 2.1

Block 2 - Message Type

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.3

Block 3 - Message not supported

Type / Role: n8n-nodes-evolution-api.evolutionApi - evolutionApi
Config choices: Version 1

Block 4 - Transcribe a recording

Type / Role: @n8n/n8n-nodes-langchain.googleGemini - googleGemini
Config choices: Version 1

Block 5 - Audio

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 6 - Get base64 audio

Type / Role: n8n-nodes-evolution-api.evolutionApi - evolutionApi
Config choices: Version 1

Block 7 - Get base64 image

Type / Role: n8n-nodes-evolution-api.evolutionApi - evolutionApi
Config choices: Version 1

Block 8 - Edit Fields

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 9 - Convert to image

Type / Role: n8n-nodes-base.convertToFile - convertToFile
Config choices: Version 1.1

Block 10 - Convert to audio

Type / Role: n8n-nodes-base.convertToFile - convertToFile
Config choices: Version 1.1

Block 11 - Analyze an image

Type / Role: @n8n/n8n-nodes-langchain.googleGemini - googleGemini
Config choices: Version 1

Block 12 - Google Gemini Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
Config choices: Version 1

Block 13 - Simple Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 14 - Archestrator Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2.2

Block 15 - Get base64 document

Type / Role: n8n-nodes-evolution-api.evolutionApi - evolutionApi
Config choices: Version 1

Block 16 - Convert to document

Type / Role: n8n-nodes-base.convertToFile - convertToFile
Config choices: Version 1.1

Block 17 - Analyze document

Type / Role: @n8n/n8n-nodes-langchain.googleGemini - googleGemini
Config choices: Version 1

Block 18 - Document

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 19 - MCP Server Google Calendar

Type / Role: @n8n/n8n-nodes-langchain.mcpTrigger - mcpTrigger
Config choices: Version 2

Block 20 - Send message

Type / Role: n8n-nodes-evolution-api.evolutionApi - evolutionApi
Config choices: Version 1

Block 21 - MCP Calendar

Type / Role: @n8n/n8n-nodes-langchain.mcpClientTool - mcpClientTool
Config choices: Version 1.1

Block 22 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 23 - Image

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 24 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Showing the first 24 of 31 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	WhatsApp assistant with Gemini AI for calendar management via Evolution API
Complexity	advanced
Nodes	31
Categories	Support Chatbot, AI Chatbot
Author	Pedro Protes
Published	17 Nov 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/10944/10944.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Support Chatbot workflows AI Chatbot workflows

Frequently asked questions

What does WhatsApp assistant with Gemini AI for calendar management via Evolution API do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Support Chatbot, AI Chatbot use case.

Pedro Protes

1 workflow

Nodes

n8n-nodes-base.webhook n8n-nodes-base.switch n8n-nodes-evolution-api.evolutionapi @n8n/n8n-nodes-langchain.googlegemini n8n-nodes-base.set n8n-nodes-base.converttofile @n8n/n8n-nodes-langchain.lmchatgooglegemini @n8n/n8n-nodes-langchain.memorybufferwindow

Complexity

advanced

Published 17 Nov 2025

Likes 0

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Install path: /data/workflows/10944/10944.json

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WhatsApp assistant with Gemini AI for calendar management via Evolution API

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

AI Agent that uses MCP Server to execute actions requested via Evolution API.

🔧 How it works

🗒️ Requirements

✔️ How to set up

🦾 how to adapt it?

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Webhook

Block 2 - Message Type

Block 3 - Message not supported

Block 4 - Transcribe a recording

Block 5 - Audio

Block 6 - Get base64 audio

Block 7 - Get base64 image

Block 8 - Edit Fields

Block 9 - Convert to image

Block 10 - Convert to audio

Block 11 - Analyze an image

Block 12 - Google Gemini Chat Model

Block 13 - Simple Memory

Block 14 - Archestrator Agent

Block 15 - Get base64 document

Block 16 - Convert to document

Block 17 - Analyze document

Block 18 - Document

Block 19 - MCP Server Google Calendar

Block 20 - Send message

Block 21 - MCP Calendar

Block 22 - Sticky Note

Block 23 - Image

Block 24 - Sticky Note1

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions