- NEW
- EDIT
- AUDIT
- MANUAL
Short answer
How can I manage my vision workflows with AI?
You use natural language to tell your AI to build, edit, or audit your vision pipelines. It handles the technical configuration while you focus on the logic. You'll see exactly how the AI maps your commands to active vision tasks.
Where every command lands.
Pipeline management outcomes
Your AI translates your intent into these four operational states.
NEW
Active pipelines
The AI builds new vision tasks based on your descriptions. You get a running pipeline ready to process video feeds.
EDIT
Updated configs
Change how a pipeline behaves without touching code. Your AI modifies existing settings to match your new requirements.
AUDIT
Current status
Get a full list of what is currently running. Your AI pulls the state of all active vision workflows for you.
MANUAL
Human oversight
The AI flags configuration errors or logic gaps. You step in to make the final decision on complex visual logic.
The workflow
What your AI does when a command arrives.
The AI acts as the bridge between your plain English and the EyePop.ai engine.
Identify intent
Your AI looks at your request to see if you want to start something new or change what is already running.
list_popsCheck existing setup
Before making changes, the AI pulls the current settings to ensure the new command makes sense.
get_pop_configExecute changes
The AI sends the specific configuration instructions to the vision engine to apply your updates.
create_popVerify deployment
The AI checks the updated list of pipelines to confirm the new configuration is live and active.
list_pops
Try it
Copy these to start.
Use these prompts to kick off your first vision task.
Starting points
Swap the bracketed text for your specific camera names or detection targets.
EyePop.ai Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_cGrHSw5koZ6157myj6LuxsjlFf5P2wK2JZdQoPtm/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — EyePop.ai capabilities are ready to use.
{
"mcpServers": {
"eyepopai-mcp": {
"url": "https://edge.vinkius.com/vk_preview_cGrHSw5koZ6157myj6LuxsjlFf5P2wK2JZdQoPtm/mcp"
}
}
}Create a new vision pipeline for the North Gate camera to detect unauthorized vehicles.
Show me all the vision pipelines currently running in the warehouse.
Update the configuration for the loading dock pipeline to increase the sensitivity of person detection.
Get the current settings for the perimeter security pipeline.
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect EyePop.ai once, then ask.
Click the link to connect your account. Your credentials stay encrypted, and you can immediately start managing pipelines in your preferred AI client.
Connect EyePop.ai to your AIFAQ
How the management task behaves
- 01
Can the AI delete a pipeline for me?
No. The AI can create and modify configurations, but it cannot delete existing pipelines.
- 02
Can I use this to view the actual video feed?
No. This tool manages the configuration and status of the pipelines, not the raw video stream itself.
- 03
Does the AI handle the camera hardware setup?
No. The AI manages the software pipelines that process the data, but it does not interact with physical camera hardware.
- 04
How do I know if a command worked?
The AI will confirm the action by checking the updated list of active pipelines.
- 05
Can I change detection sensitivity through chat?
Yes. You can tell the AI to adjust the configuration of an existing pipeline.
More questions about EyePop.ai? The Connector page answers them. See everything the EyePop.ai Connector can do
Connect EyePop.ai to Claude, Cursor, ChatGPT & more
