How to Use the EyePop.ai MCP in Cursor

Q: How does Cursor use EyePop.ai to write image processing code?

Your Cursor agent calls analyzeimage to get real detection payloads. Cursor uses an MCP connection to feed this live JSON metadata back into the editor, allowing the AI to generate accurate parsing code.

Q: Can I test my video analysis pipelines directly in Cursor?

Yes. Run analyzevideo inside the Cursor chat to process sample video files. The editor displays the temporal detection data, letting you write and debug video tracking algorithms with real-world inputs.

Q: How do I check if my EyePop.ai API keys are working in Cursor?

Trigger checkeyepopstatus in Cursor to verify your API credentials. The tool returns your connection state, ensuring your development environment is fully authorized before you start coding.

Q: How do I configure new EyePop.ai pipelines from Cursor?

Use createpop to define a new visual pipeline within the editor. Your agent sets up the pipeline and retrieves its configuration via the MCP server, so you can write integration code immediately.

Write computer vision code in Cursor using live object detection coordinates and pipeline metadata from EyePop.ai.

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Connect EyePop.ai MCP to Cursor

Create your Vinkius account to connect EyePop.ai to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup EyePop.ai with Cursor

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Inject real-time model data into your Cursor workspace

The `analyze_image` tool sends test images to EyePop.ai and feeds the exact JSON response into your Cursor agent. This lets the agent write parser code based on real bounding boxes and labels instead of guessing the API schema. Using this live feedback loop, the agent writes reliable validation logic for your custom image processing scripts.

Configure visual pipelines inside Cursor

The `create_pop` tool allows your Cursor agent to set up new visual pipelines on your EyePop.ai account without leaving the editor. Your agent drafts the configuration, executes the tool, and instantly gets the new pipeline details. You run `get_pop` to verify the pipeline's active state and model configuration. This tight integration means you build, test, and write code against new computer vision workflows in a single terminal-free session.

Verify API status and track active models

The `check_eyepop_status` tool validates your API credentials and endpoints directly within Cursor. Your agent runs this check before generating deployment code to ensure your environment variables are configured correctly. This prevents runtime errors by ensuring your code references valid model names that the EyePop.ai MCP Server actively supports.

Setup guide

Set up EyePop.ai MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the EyePop.ai MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent EyePop.ai transactions." If the MCP tools are loaded correctly, Cursor will call the EyePop.ai tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "eyepopai-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by EyePop.ai. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about EyePop.ai MCP in Cursor

Your Cursor agent calls `analyze_image` to get real detection payloads. Cursor uses an MCP connection to feed this live JSON metadata back into the editor, allowing the AI to generate accurate parsing code.

Yes. Run `analyze_video` inside the Cursor chat to process sample video files. The editor displays the temporal detection data, letting you write and debug video tracking algorithms with real-world inputs.

Trigger `check_eyepop_status` in Cursor to verify your API credentials. The tool returns your connection state, ensuring your development environment is fully authorized before you start coding.

Use `create_pop` to define a new visual pipeline within the editor. Your agent sets up the pipeline and retrieves its configuration via the MCP server, so you can write integration code immediately.

Your media files go directly from your local machine to the EyePop.ai endpoints for processing. Cursor only receives the JSON detection metadata using an ephemeral MCP link, ensuring your raw files are never stored or logged by the editor.

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