Creating a AI Slack Bot with Google Gemini

This is a POST Webhook endpoint Make sure to configure this webhook using a https:// wraper and dont use the default http://localhost:5678 as that will not be recognized by your slack webhook Once the data has been sent to your webhook, the next step will be passing it via an AI Agent to process data based on the queries we pass to our agent. To have some sort of a memory, be sure to set the slack token to the memory node. This way you can refer to other chats from the history. The final message

Integrations Used (5)

Lmchatgooglegemini

Workflow Structure (5 nodes)

100%

Webhook

Webhook to receive message

Langchain.agent

Agent

Slack

Send response back to slack channel

Langchain.lm Chat Google Gemini

Google Gemini Chat Model

Langchain.memory Buffer Window

Window Buffer Memory

Node Types:

action

default

trigger

Requires credentials

Prerequisites

No credentials required!

This workflow can be imported and used immediately.

Complexity

Simple

Great for beginners. Few nodes, straightforward setup.

Setup time: ~10 min

Score: 14/100

When to Use This Workflow

Streamline Team Communication

Automatically route notifications and updates to the right channels and people.

Reduce information overload while keeping everyone informed.

Team Notifications

Send automated alerts and updates to your team chat when important events occur.

Never miss critical updates - your team stays informed in real-time.

Real-time Response

React instantly when events happen - new orders, form submissions, or API calls.

Zero delay between trigger and action for time-sensitive workflows.

workflow.json

{
  "meta": {
    "instanceId": "84ba6d895254e080ac2b4916d987aa66b000f88d4d919a6b9c76848f9b8a7616",
    "templateId": "2370"
  },
  "nodes": [
    {
      "id": "2ce91ec6-0a8c-438a-8a18-216001c9ee07",
      "name": "Sticky Note",
      "type": "n8n-nodes-base.stickyNote",
      "position": [
        380,
        240
      ],
      "parameters": {
        "width": 407.6388140161723,
        "height": 490.24769122000794,
        "content": "## This is a POST Webhook endpoint\n\nMake sure to configure this webhook using a https:// wraper and dont use the default http://localhost:5678 as that will not be recognized by your slack webhook\n\n\nOnce the data has been sent to your webhook, the next step will be passing it via an AI Agent to process data based on the queries we pass to our agent.\n\nTo have some sort of a memory, be sure to set the slack token to the memory node. This way you can refer to other chats from the history.\n\nThe final message is relayed back to slack as a new message. Since we can not wait longer than 3000 ms for slack response, we will create anew message with reference to the input we passed.\n\nWe can advance this using the tools or data sources for it to be more custom tailored for your company.\n"
      },
      "typeVersion": 1
...