Block 1 - Sticky Note
- Type / Role
- n8n-nodes-base.stickyNote - stickyNote
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
This is an example of how we can build a slack bot in a few easy steps Before you can start, you need to o a few things 1. Create a copy of this workflow 2. Create a slack bot 3. Create a slash com...
n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.lmchatgooglegemini, @n8n/n8n-nodes-langchain.memorybufferwindow, n8n-nodes-base.slack, n8n-nodes-base.webhook, @n8n/n8n-nodes-langchain.agent
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Zacharia Kimotho.
Original n8n.io sourceThis is an example of how we can build a slack bot in a few easy steps
Before you can start, you need to o a few things
Make sure to configure this webhook using a https:// wrapper and don't 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 is relayed back to slack as a new message. Since we can not wait longer than 3000 ms for slack response, we will create a new message with reference to the input we passed.
We can advance this using the tools or data sources for it to be more custom tailored for your company.
To use the slackbot, go to slack and click on your set slash command eg /Bob and send your desired message.
This will send the message to your endpoint and get return the processed results as the message.
If you would like help setting this up, feel free to reach out to [email protected]
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.
| Workflow | Creating a AI Slack bot with Google Gemini |
|---|---|
| Complexity | intermediate |
| Nodes | 10 |
| Categories | Internal Wiki, AI Chatbot |
| Author | Zacharia Kimotho |
| Published | 29 Jul 2024 |
Use the JSON export at /data/workflows/2370/2370.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
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.
This is an example of how we can build a slack bot in a few easy steps Before you can start, you need to o a few things 1. Create a copy of this workflow 2. Create a slack bot 3. Create a slash com...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
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 Internal Wiki, AI Chatbot use case.