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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Comet ML with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Manage machine learning experiments via Comet. track model metrics, audit project workspaces, and inspect ML run parameters directly from any AI agent.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 6 capabilities

The complete Comet ML capability set.

These are the exact actions your AI can choose when you ask it to work with Comet ML.

Capability set01 / 02

01-03

3 capabilities in this set.

Part of 6 available through Comet ML.

  1. 01

    List workspaces

    Identify bounded routing spaces inside the Headless Comet ML limits

  2. 02

    Get experiment params

    Inspect internal properties detailing API taxonomy types

  3. 03

    Get experiment

    Retrieve explicit Cloud logging tracing explicit Payload IDs

Capability set02 / 02

04-06

3 capabilities in this set.

Part of 6 available through Comet ML.

  1. 04

    Get experiment metrics

    Execute static mapping targeting exactly defined numeric bounds natively

  2. 05

    List experiments

    Discover explicit routing arrays structuring specific logged experiment limits

  3. 06

    List projects

    Perform structural extraction matching target Projects inside Comet

Observed, not estimated

811ms average. Fast in production.

Comet ML is checked daily against the live service.

Daily averagePeak 949ms
Aug 20Today
Fastest day
658ms
Slowest day
949ms
14-day trend
Slowing+33%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 6 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Comet ML, so you can see the experience inside your AI.

It does not authenticate your account with Comet ML. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Comet ML Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_C2PxqYqwffQi3V41WE8jlPynFSP048sA8SVR1PFT/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Comet ML capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "comet-ml-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_C2PxqYqwffQi3V41WE8jlPynFSP048sA8SVR1PFT/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

FAQ

Questions Comet ML owners ask.

  • 01

    Can my agent retrieve real-time metrics from an active ML run?

    Yes. Use the 'get_experiment_metrics' capability with the experiment key. The agent will pull the latest numeric logged endpoints, allowing you to monitor loss, accuracy, and other custom metrics as they are generated.

  • 02

    How do I audit the parameters used in a specific experiment?

    Provide the experiment key to your agent. The 'get_experiment_params' capability extracts all logged ML properties, helping you verify hyperparameters like learning rates, batch sizes, and model architectures.

  • 03

    Can I see a list of all experiments within a specific project?

    Absolutely. Use the 'list_experiments' capability with the project ID. Your agent will surface all ML runs within that project, including their status and metadata, so you can quickly identify the results you need.

Explore

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