How to Use the DeepInfra (Serverless LLM Inference) MCP in Cline

Give Cline direct access to serverless LLM inference and custom embeddings right inside VS Code.

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Connect DeepInfra (Serverless LLM Inference) MCP to Cline

Create your Vinkius account to connect DeepInfra (Serverless LLM Inference) to Cline 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 DeepInfra (Serverless LLM Inference) with Cline

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Execute Specialized Models

The `run_native_inference` tool executes specialized models like OCR or speech-to-text directly from your editor. You provide the model name and payload, and the agent handles the network request. Cline writes a Python script requiring audio transcription, hits the native endpoint to verify the payload format, and updates your code based on the actual response. The agent tests its own logic against live inference data.

Consult Secondary LLMs

Triggering `create_chat_completion` lets your agent consult secondary LLMs for complex debugging. You tell the agent to analyze a difficult bug, and it decides to ask a different model for a second opinion. When Cline hits a wall with a specific framework, it queries DeepSeek-V3 through the API, reads the suggested fix, and writes the patch into your repository. You watch the autonomous workflow happen in real time.

Build Vector Search with Cline MCP Server

Applying `create_embedding` turns text into vector arrays using this Cline MCP Server connection. You request a semantic search feature, and the agent handles the vectorization step by calling the API. Your AI client reads the array length returned by the model and adjusts your database schema accordingly. It writes the insertion logic, runs the tests end-to-end, and stages the commit without asking for help.

Setup guide

Set up DeepInfra (Serverless LLM Inference) MCP in Cline

Prerequisites

VS Code with Cline extension installed
Active Vinkius subscription with a valid endpoint token

1

Open Cline MCP settings

Click the Cline icon in the VS Code sidebar to open the Cline panel. Then click the MCP Servers icon (server stack) at the top-right corner of the panel.
2

Add a remote server

Click "Remote Servers" at the top, then click "Add Remote MCP". In the Name field, type deepinfra-serverless-llm-inference-mcp. In the URL field, paste your Vinkius endpoint: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp. Get your token from cloud.vinkius.com.
3

Enable the server

After saving, the server appears in the Cline MCP panel. Toggle the switch to enable it. The status indicator turns green when the connection is live.
4

Start using tools

Return to the Cline chat and ask: "Check my latest DeepInfra (Serverless LLM Inference) refund status." Cline will discover the available tools and request your approval before invoking each one — giving you full control over every action.

Cline MCP Settings

{
  "mcpServers": {
    "deepinfra-serverless-llm-inference-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

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Common questions about DeepInfra (Serverless LLM Inference) MCP in Cline

Open the Cline sidebar, click the MCP Servers icon, and navigate to the Remote Servers tab. Paste your Vinkius Streamable HTTP transport URL and you are ready to start coding.

It does this by default. The agent uses the native inference endpoint to pass test images to the model and writes the parsing logic based on real API outputs.

The tool accepts standard text inputs and returns the vector array defined by the specific model you target. You configure the dimension requirements in your prompt.

Yes. The agent gathers data from the inference endpoints and includes the results in its regular workflow. You review the diffs just like any other task.

Authentication happens entirely on the Vinkius side. Your VS Code workspace only holds a single endpoint token, meaning your actual credentials and raw test files never touch the agent's local memory.

Use it with your favorite AI tools

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