Verbinden Sie Baseten mit ChatGPT, Claude und Gemini

• 01 / 03Deployments prüfen
• 02 / 03Vorhersagen ausführen
• 03 / 03Secrets prüfen

Schnellster Tag

703ms

Langsamster Tag

1169ms

14-Tage-Trend

Verlangsamend+22%

Baseten Connector

Alles bereit. Wählen Sie Ihren MCP-Client und folgen Sie den Einrichtungsschritten.

Connector-Linkhttps://edge.vinkius.com/vk_preview_Iok4x74580t8DfXgX0kQJnXTan6vttePrqZ5XRGU/mcpKopieren

Claude Desktop

Folgen Sie den Schritten unten, um sich in Sekunden zu verbinden.

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 — Baseten capabilities are ready to use.

Konfiguration · claude_desktop_config.jsonKopieren

{
  "mcpServers": {
    "baseten-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_Iok4x74580t8DfXgX0kQJnXTan6vttePrqZ5XRGU/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

Schritt-für-Schritt-Anleitungen für jeden Client finden Sie im Guide. Verbinden

Geführte Einrichtung für Claude? Baseten in Claude und anderen KI-Tools einrichten

Alle KI-Clients ansehen, mit denen dieser Connector funktioniert ↑

• 01

  ML Engineers

  Führen Sie Test-Payloads sofort auf Deployments aus, ohne lokale Python-Notebooks starten zu müssen.

• 02

  DevOps/SREs

  Auditieren Sie laufende Deployment-Ressourcen und verifizieren Sie Replika-Zustände zuverlässig direkt aus Ihrer IDE.

• 03

  AI Researchers

  Überprüfen Sie Versions-Schemas und verwalten Sie komplexe Inference-Pipeline-Architekturen schnell und effizient.

• 01

  Does this MCP require me to use a specific AI client?

  No. You connect your preferred agent, as long as it is MCP-compatible. This allows you to use your existing setup, whether it's Claude, Cursor, or VS Code.

• 02

  Can I use this to manage models that aren't deployed yet?

  Yes. You can use the list_models capability to see all managed models and get their configurations, even if they aren't currently running a live deployment.

• 03

  What kind of data can I send for a prediction?

  You must provide tensor shapes or a dictionary that strictly matches the deployed instance. The MCP handles running the serverless inference prediction with that payload.

• 04

  Is the secret listing secure?

  Yes. The list_secrets capability only enumerates the active environment secrets without showing the actual plaintext values, keeping your credentials secure.

• 05

  Is this just a directory of Baseten features?

  No. Vinkius hosts and manages this MCP. It's a ready-to-use product that executes the commands directly through your agent, eliminating the need to switch contexts.

• 06

  Can the AI agent run a prediction directly against my hosted model?

  Yes. By pushing a correctly formatted JSON payload to the 'predict' capability, the agent securely triggers inference on the GPU instances, returning the exact calculated response data transparently to your editor context.

• 07

  Is my workspace and environmental secret data kept safe?

  Baseten secret fetching natively obscures variable values. When you use 'list_secrets', the agent simply evaluates the key names and identifiers existing across your environment to verify configurations without exposing plaintext passwords.

• 08

  How do I check auto-scaling configurations for an explicitly deployed model?

  You can examine exactly how instances are managed by using 'get_deployment'. Tell the agent to target an active deployment ID and it maps the scaling limits, replica status, and container bounds out-of-the-box.

• 

  Modelbit (ML Model Deployments) KI-Connector

  Deploy and call machine learning models directly from your AI agent using Modelbit's inference endpoints.

  Ansehen
• 

  DeepInfra (Serverless LLM Inference) KI-Connector

  Run top-tier LLMs, image generation, and embeddings via DeepInfra's serverless infrastructure directly from yo

  Ansehen
• 

  Monster API (Serverless GPU & AI Model Hosting) KI-Connector

  Access powerful AI models for image generation, text-to-speech, and transcription via serverless GPU infrastru

  Ansehen
• 

  Modal (Serverless AI Infrastructure) KI-Connector

  Manage serverless compute via Modal — audit active apps, track GPU deployments, and monitor network volumes.

  Ansehen

Vorschläge

• 

  Scale Prediction Model KI-Connector

  Predicts mineral scale formation in oilfield operations using water chemistry and environmental data.

  Ansehen
• 

  NVIDIA API Catalog KI-Connector

  Cloud Engine proxy running native foundational completions natively utilizing active Nemotron and Llama3 archi

  Ansehen
• 

  Vercel KI-Connector

  Deploy frontend applications instantly with a platform optimized for Next.js, serverless functions, and edge c

  Ansehen
• 

  Cerebras Inference KI-Connector

  Access lightning-fast AI inference via Cerebras Wafer-Scale Engine — generate chat completions, manage models,

  Ansehen