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Connect Deepinfra Serverless LLM Inference to your AI

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Run high-performance open-source models directly from your AI client.

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

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through DeepInfra.

  1. 01

    Run native inference

    This capability runs native inference for models that don't follow standard OpenAI specifications. Use it for specialized tasks like speech-to-text, OCR, or video generation.

  2. 02

    Create embedding

    This capability generates text embeddings via DeepInfra. It's used to convert text into high-dimensional vectors for semantic search or RAG.

  3. 03

    Generate image

    This capability creates images from text prompts. It uses models like FLUX-1 or Stable Diffusion to turn your descriptions into visuals.

  4. 04

    Create chat completion

    This capability handles chat completions using various LLMs. You provide the model name and your messages to get a text response.

Real work

What teams actually run

01

RAG Pipeline Development

Use the embedding capability to turn documents into vectors for semantic search.

02

Automated Content Creation

Generate text and images in bulk using serverless LLM and image models.

03

Custom AI Workflows

Run specialized OCR or speech-to-text tasks through native inference.

04

Local Coding Assistance

Power your IDE with high-end models like DeepSeek for better code generation.

Automate a task

Put DeepInfra to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

DeepInfra works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put DeepInfra to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

892ms average. Fast in production.

DeepInfra is checked daily against the live service.

Daily averagePeak 1117ms
Oct 3Today
Fastest day
749ms
Slowest day
1117ms
14-day trend
Stable0%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 4 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 DeepInfra, so you can see the experience inside your AI.

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

DeepInfra Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_RMvS2UlIMhdShOjNbZfqar6XAZE9QfzTMbaejxJY/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 — DeepInfra capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "deepinfra-serverless-llm-inference-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_RMvS2UlIMhdShOjNbZfqar6XAZE9QfzTMbaejxJY/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

Guided setup for Claude? Set up DeepInfra in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work DeepInfra owners hand off.

This MCP is built for technical users who need high-performance model access without the headache of managing GPUs.

  • 01

    Developers

    Integrate powerful LLMs into coding workflows without managing infrastructure.

  • 02

    Content Creators

    Generate high-quality images and text variations inside their workspace.

  • 03

    Data Engineers

    Build semantic search pipelines using serverless embedding endpoints.

FAQ

Questions DeepInfra owners ask.

  • 01

    How do I connect this MCP to my AI client?

    You subscribe to the MCP on Vinkius and enter your DeepInfra API Token. Once connected, you can use it immediately in Claude, Cursor, Windsurf, or other compatible clients.

  • 02

    Which models can I use with this MCP?

    You can access a wide range of open-source models including DeepSeek-V3, Llama 3.3, and FLUX-1 via DeepInfra's infrastructure.

  • 03

    Do I need to manage my own GPUs?

    No. This MCP uses DeepInfra's serverless infrastructure, so you don't have to manage or host any hardware.

  • 04

    Can I use this for image generation?

    Yes. You can use the generate_image capability to create visuals from text prompts using models like FLUX or Stable Diffusion.

  • 05

    What happens if a model doesn't follow OpenAI specs?

    You can use the run_native_inference capability to access specialized models for tasks like OCR or speech-to-text that don't follow standard specs.

  • 06

    Which LLM models can I use with the chat capability?

    You can use any model hosted on DeepInfra, such as deepseek-ai/DeepSeek-V3 or meta-llama/Llama-3.3-70B-Instruct, by passing the model name to the create_chat_completion capability.

  • 07

    How do I generate images using FLUX or Stable Diffusion?

    Use the generate_image capability. Simply provide the model name (e.g., black-forest-labs/FLUX-1-schnell) and your text prompt to receive the generated image URL.

  • 08

    What is the 'run_native_inference' capability used for?

    It is used for models that don't follow the OpenAI chat/image spec, such as audio transcription (Whisper), specialized OCR models, or your own private model deployments on DeepInfra.

Explore

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