How to Use the EyePop.ai MCP in Claude Code

Q: How to add EyePop.ai to Claude Code?

Use the command claude mcp add --transport http -- . It registers the server so you can use it in any terminal session.

Q: How do I list models via Claude Code?

Simply run the tool listmodels. It prints the available models directly to your stdout for easy piping.

Q: Does Claude Code log EyePop.ai usage?

The CLI logs all interactions in your /.claude.json configuration and chat history. You can audit your tool calls at any time.

Connect the EyePop.ai MCP Server to Claude Code for headless video analytics in your terminal.

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Connect EyePop.ai MCP to Claude Code

Create your Vinkius account to connect EyePop.ai to Claude Code 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 Claude Code

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Headless analysis with Claude Code

Pipe local files into `analyze_image` or `analyze_video` directly from your terminal session. It works perfectly in CI/CD pipelines where you need automated detection results. No GUI is required for these operations. You get the raw JSON back for further processing in your shell scripts.

Automate pipeline creation in Claude Code

Use `create_pop` to initialize your visual pipelines via command line. It's the fastest way to set up new environments for automated testing. You can script these calls in your build process. It makes your infrastructure as code approach much easier to manage.

Monitor status with Claude Code

Run `check_eyepop_status` to ensure your connection is healthy before starting a batch job. It's an essential step for reliable automation. If the status returns an error, your scripts can catch it immediately. It prevents broken builds caused by connectivity issues.

Setup guide

Set up EyePop.ai MCP in Claude Code

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see eyepopai-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest EyePop.ai transactions." It will automatically discover and invoke the available EyePop.ai tools.

Terminal

claude mcp add --transport http eyepopai-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Get your connection token →

Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
2

Add the EyePop.ai MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

{
  "mcpServers": {
    "eyepopai-mcp": {
      "type": "url",
      "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 Claude Code

Use the command `claude mcp add --transport http -- `. It registers the server so you can use it in any terminal session.

Yes. Since it supports HTTP transport, you can run the agent in headless mode inside your CI/CD workflow.

Your connection is authenticated via your endpoint token. The MCP server processes your video data without persistent storage.

Simply run the tool `list_models`. It prints the available models directly to your stdout for easy piping.

The CLI logs all interactions in your ~/.claude.json configuration and chat history. You can audit your tool calls at any time.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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