Verbinden Sie Sambanova AI Inference mit ChatGPT und Claude

• 01 / 03Strukturierte Daten erhalten
• 02 / 03Embeddings erstellen
• 03 / 03Open Source Modelle ausführen

Schnellster Tag

748ms

Langsamster Tag

1136ms

14-Tage-Trend

Verlangsamend+37%

SambaNova Connector

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

Connector-Linkhttps://edge.vinkius.com/vk_preview_z52tsMdkFaoCTCBeg6u7bbxNhhnjcT0r5KXU6hjj/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 — SambaNova capabilities are ready to use.

Konfiguration · claude_desktop_config.jsonKopieren

{
  "mcpServers": {
    "sambanova-ai-inference-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_z52tsMdkFaoCTCBeg6u7bbxNhhnjcT0r5KXU6hjj/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? SambaNova in Claude und anderen KI-Tools einrichten

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

• 01

  KI-Ingenieure

  Entwickler von Echtzeitanwendungen, die eine geringe Latenz und einen hohen Durchsatz erfordern.

• 02

  Softwareentwickler

  Nutzer, die eine kosteneffiziente und schnellere Alternative zu Standard-LLM-Anbietern suchen.

• 03

  Data Scientists

  Experten, die Embeddings für groß angelegte Wissensdatenbanken in hohem Maßstab generieren müssen.

• 01

  Which models can I use with this MCP?

  You can access models like Meta-Llama-3.3-70B-Instruct, DeepSeek-V3.1, and MiniMax-M2.7.

• 02

  How do I connect it to my AI client?

  Once you subscribe on Vinkius, you can connect it to Claude, Cursor, Windsurf, or any other MCP-compatible client with one click.

• 03

  What makes the inference speed different?

  The speed comes from SambaNova's specialized SN40L chips and DataScale infrastructure, which are designed for high-speed dataflow.

• 04

  Can I use this for RAG?

  Yes, you can use the create_embedding capability to generate text representations for your retrieval-augmented generation workflows.

• 05

  Is this compatible with OpenAI capabilities?

  Yes, the create_chat_completion capability is compatible with the OpenAI Chat Completions API format.

• 06

  Which models are available for chat completions?

  You can use create_chat_completion with models like Meta-Llama-3.3-70B-Instruct, DeepSeek-V3.1, and MiniMax-M2.5 for high-speed text generation.

• 07

  Can I generate embeddings for my RAG pipeline?

  Yes! Use the create_embedding capability with models like E5-Mistral-7B-Instruct to create vectorized representations of your text data.

• 08

  What is the difference between create_chat_completion and create_response?

  create_chat_completion follows the standard OpenAI chat format, while create_response is a stateless API designed specifically for agentic workflows, returning typed output items.

• 

  DeepInfra (Serverless LLM Inference) KI-Connector

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

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• 

  Cerebras Inference KI-Connector

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

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• 

  Mistral AI (Frontier LLMs & Embeddings) KI-Connector

  Manage AI inference via Mistral — execute chat completions, generate RAG embeddings, and audit frontier models

  Ansehen
• 

  Fireworks AI KI-Connector

  Empower LLM applications via Fireworks AI — perform ultra-fast chat completions, generate embeddings and image

  Ansehen

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  Moscow History, Heritage & High-Rises KI-Connector

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