Claude and other AIs

How to set up Scale Prediction Model in Claude and other AIs

Set up in seconds, once. From then on, Scale Prediction Model answers in Claude, in ChatGPT, in Gemini — in every AI you use: the same link, the same governance, nothing to rebuild.

Ask AI about this guide

Step by step, for each client

Connecting Scale Prediction Model in each client

The same hosted link plugs into every client below. Pick the one you use — each setup takes seconds — and start a new chat.

Claude

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Claude

About a minute, right in your Claude settings

  1. 1In Claude, open Customize and choose Connectors (claude.ai or the desktop app).
  2. 2Click +, choose Add custom connector, and paste your Scale Prediction Model link as the remote MCP server URL.
  3. 3Click Add and start a new chat. Ask for something real: Scale Prediction Model is now part of your Claude.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

ChatGPT

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to ChatGPT

About a minute, right in your ChatGPT settings

  1. 1In ChatGPT, open Settings, choose Apps & Connectors, and turn on Developer mode under Advanced settings.
  2. 2Click Create, name it, and paste your Scale Prediction Model link as the MCP server URL. Choose No authentication and check “I trust this application”.
  3. 3Create it, start a new chat, and switch the connector on via the + menu. Ask for something real: Scale Prediction Model is now part of your ChatGPT.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Gemini

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Gemini

About a minute, right in your terminal

  1. 1Open the Gemini CLI in your terminal.
  2. 2Run: gemini mcp add --transport http Scale Prediction Model <your link>. Your Scale Prediction Model link above is the HTTP URL.
  3. 3Run /mcp and confirm the status shows CONNECTED. Scale Prediction Model is now part of your Gemini.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Perplexity

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Perplexity

A few minutes, in the Perplexity Mac app

  1. 1In the Perplexity Mac app, open Account, choose Connectors, and click Add Connector.
  2. 2In the Simple tab, choose MCP Connector, name it, and add the bridge command with your Scale Prediction Model link: npx mcp-remote <your link>. The link above is the URL.
  3. 3Click Save and check it shows Running, then turn the connector on under Sources on the homepage. Scale Prediction Model is now part of your Perplexity.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Grok

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Grok

About a minute, at grok.com/connectors

  1. 1In Grok, open grok.com/connectors and click New Connector.
  2. 2Choose Custom, name it, and paste your Scale Prediction Model link as the remote MCP server URL.
  3. 3Save and enable it, finish the browser authorization if prompted, and ask Grok something real. Scale Prediction Model is now part of your Grok.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Microsoft Copilot

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Copilot

About a minute, in VS Code's Copilot Chat

  1. 1In VS Code, open the Copilot Chat panel, click the tools icon and select the + icon, or run MCP: Add Server from the Command Palette.
  2. 2Choose your scope, name the server, and paste your Scale Prediction Model link as the server URL with HTTP transport.
  3. 3Confirm the server appears in your MCP list, then ask Copilot something real. Scale Prediction Model is now part of your Copilot.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Cursor

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Cursor

About a minute, in Cursor

  1. 1Open Customize in the Cursor sidebar (or create .cursor/mcp.json in your project).
  2. 2Add an MCP server named Scale Prediction Model with the url field set to your link. The link above is the URL.
  3. 3Save, enable the server, and ask something real. Scale Prediction Model is now part of Cursor.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

VS Code

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to VS Code

About a minute, in VS Code

  1. 1Run MCP: Add Server from the Command Palette (or create .vscode/mcp.json in your project).
  2. 2Add a server named Scale Prediction Model with type http and your link as the url. The link above is the URL.
  3. 3Save and ask something real in Copilot Chat. Scale Prediction Model is now part of VS Code.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Windsurf

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Windsurf

About a minute, in Cascade

  1. 1In Cascade, click the MCPs icon (or go to Settings, Cascade, MCP Servers).
  2. 2Edit mcp_config.json and add Scale Prediction Model with the serverUrl field set to your link. The link above is the URL.
  3. 3Save and ask something real. Scale Prediction Model is now part of Windsurf.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

JetBrains

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to JetBrains

About a minute, in Settings

  1. 1Go to Settings, Tools, AI Assistant, Model Context Protocol (MCP).
  2. 2Click Add and add Scale Prediction Model with the url field set to your link. The link above is the URL.
  3. 3Click OK and Apply, check the Status column, and ask something real. Scale Prediction Model is now part of your IDE.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Cline

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Cline

About a minute, in the Cline panel

  1. 1In the Cline panel, click the MCP Servers icon and open the Remote Servers tab.
  2. 2Add a server named Scale Prediction Model with your link as the Server URL and Streamable HTTP as the transport. The link above is the URL.
  3. 3Click Add Server and ask something real. Scale Prediction Model is now part of Cline.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

LangChain

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to LangChain

About a minute, in your code

  1. 1Install LangChain with the mcp extra: pip install "langchain[mcp]".
  2. 2Create an MCPAdapter with your Scale Prediction Model link: MCPAdapter("<your link>"). The link above is the URL.
  3. 3Call list_tools and pass the tools to your agent. Scale Prediction Model is now part of your LangChain agent.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Vercel AI SDK

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to the Vercel AI SDK

About a minute, in your code

  1. 1Install the MCP client: npm install @ai-sdk/mcp, and import createMCPClient from '@ai-sdk/mcp'.
  2. 2Create the client with your Scale Prediction Model link as the transport: { type: 'http', url: '<your link>' }. The link above is the URL.
  3. 3Call client.tools() and pass the tools to streamText. Scale Prediction Model is now part of your AI SDK app.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Lovable

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Lovable

About a minute, in the Connectors catalog

  1. 1Open Connectors, select the + button in the top right of the catalog, and choose MCP server.
  2. 2Name the server and paste your Scale Prediction Model link as the Server URL. The link above is the URL.
  3. 3Choose No authentication and click Add server, then ask Lovable something real. Scale Prediction Model is now part of Lovable.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Z.ai

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Z.ai

About a minute, in ZCode settings

  1. 1Open Settings, MCP Servers, then click New MCP Server in the upper-right corner.
  2. 2Choose the User scope, name it, and keep the type as HTTP. Paste your Scale Prediction Model link as the service URL. The link above is the URL.
  3. 3Click Add and confirm the server is enabled in the list, then ask something real. Scale Prediction Model is now part of Z.ai.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Raycast

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Raycast

A few minutes, in Raycast Pro

  1. 1Search for the Install MCP Server command (or open Manage MCP Servers and choose Install New Server).
  2. 2Give the server a name and icon, select HTTP as the transport, and paste your Scale Prediction Model link as the URL. The link above is the URL.
  3. 3Press Install MCP Server and confirm the status shows Running, then ask something real. Scale Prediction Model is now part of Raycast.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Qwen Code

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Qwen Code

About a minute, in your terminal

  1. 1Run: qwen mcp add --transport http Scale Prediction Model <your link>. The link above is the URL.
  2. 2Prefer a config file? Add it to ~/.qwen/settings.json (user) or .qwen/settings.json (project) with the httpUrl field. The link above is the URL.
  3. 3Enter /mcp in the chat to confirm the server appears. Scale Prediction Model is now part of Qwen Code.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Kimi Code

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Kimi Code

About a minute, in the TUI

  1. 1Run /mcp-config in the Kimi Code TUI to add a server interactively (or edit mcp.json directly).
  2. 2Add a server named Scale Prediction Model with your link in the url field. The link above is the URL.
  3. 3Run /mcp to confirm the status, then ask something real. Scale Prediction Model is now part of Kimi Code.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Le Chat

Scale Prediction Model Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

Connecting Scale Prediction Model to Le Chat

About a minute, in Connectors

  1. 1In Le Chat, open Connectors and choose to add a custom connector.
  2. 2Paste your Scale Prediction Model link as the remote MCP server URL. The link above is the URL.
  3. 3Save and authorize, then ask something real. Scale Prediction Model is now part of Le Chat.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "scale-prediction-model-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp"
    }
  }
}

Claude and other AIs + Scale Prediction Model

One chat. Your Scale Prediction Model, live inside Claude and other AIs.

Real prompts, answered with live data. This is the kind of conversation you will have in Claude and other AIs once the link is in.

Waiting for input…

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

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

These prompts ship with the Scale Prediction Model Connector. Once yours is connected, they work in your chats.

The full capability set, the prompts and the observed latency live on the Scale Prediction Model Connector page.

Mission Control

See everything your agents do in Scale Prediction Model.

When your agents run a tool in Scale Prediction Model, it happens on the client side: you see the answer in the chat, but not the request itself, what data it carried, or whether a rule was broken.

Now every move lands on your screen.

Every execution is recorded, enforced, and shown to you: what ran, what it returned, what was blocked, and why.

AI Briefing
Upgrade to unlock

Know exactly what needs your attention before you even look at the charts. One briefing. The full picture. The next move.

Requests
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API 88ms · Overhead 54ms
Vinkius Reliability
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Agent 280 · Upstream 47 · Vinkius 15
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AI tokens processed
DLP Protected
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Sensitive data redacted
Cost Saved
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AI Agents Activities

last 30 days
30d agotoday

Request Volume & Latency

requests latency

Every request your agents make through Scale Prediction Model is logged, enforced and auditable. See how AI Governance turns agent activity into accountability, and what it means for your Scale Prediction Model workflows.

What sets us apart

It's not just the Connector that stays safe. Everything your agents do through it is.

Connecting Scale Prediction Model to your AI is step one. But an open line between your agents and Scale Prediction Model is only half the story: without protection, every action they take runs unguarded.

That's why protection doesn't stop at the door.

Every action your agents take through the Connector runs inside our infrastructure: signed activity logs, automatic key rotation, spending limits that pause instead of surprise, and a sandbox that isolates every execution.

01

Tamper Proof Activity Log

Every request your agents make in Scale Prediction Model is recorded and signed, so any change to the history becomes detectable.

02

Automatic Key Rotation

We rotate security keys every 24 hours. Your Scale Prediction Model connection stays protected without any manual work.

03

Spending Protection

We enforce the spending limit you choose and pause actions that exceed it until approval is received. Your Scale Prediction Model actions never surprise you.

04

Isolated Sandbox

Every execution through Scale Prediction Model runs isolated, with 34+ security rules covering memory, CPU, network access, file handling and execution.

05

Security Event Streaming

Security events flow to Splunk, Datadog or your own webhook, so Scale Prediction Model activity lands in the tools you already rely on.

06

Instant Resume

Idle connections resume in 3 to 5 ms while preserving their state, keeping your conversations responsive across every client.

07

Malicious File Protection

We detect compressed files designed to exhaust system resources and block them before they ever reach Scale Prediction Model.

08

Credential Validation

We test your Scale Prediction Model credentials before saving them. Invalid credentials are rejected instead of being stored.

09

Separate Usage Limits

Usage stays isolated per account, so activity in one connection never consumes another account's allowance.

One Connector, one link, and the whole operation is protected. Not just the connection: everything your agents do through it.

These guarantees are not add-ons: they are the infrastructure every Scale Prediction Model connection runs on. Read how our infrastructure protects everything your agents do, end to end.

Inside Vinkius

Get Scale Prediction Model ready for your AI. It's easy.

You choose Scale Prediction Model from the Vinkius Catalog and get one connection link. That's it.

  1. You choose Scale Prediction Model

    You find Scale Prediction Model in the Catalog and install the Connector with one click.

    Scale Prediction Model

    Active

    Enable Connector
    Activating…

  2. You add the link in your AI client

    Vinkius gives you one connection link. Add it to the client you use — the exact steps for each client are in the section above — and Scale Prediction Model is live everywhere in one move.

    Token generated successfully

    MCP Connection URL

    https://edge.vinkius.com/vk_preview_jRNFc64QZyuRJWrQwJNmFLVrNa4Wchr71RLLujlB/mcp

    Connection Token

    vk_live_••••••••
    Go to Dashboard

Set it up once. Use Scale Prediction Model with the AI you already use.

FAQ

Claude access questions.

  • 01

    Does this work on claude.ai and in the Claude desktop app?

    Yes. You add the same link under Customize and Connectors in both, and your chats work the same in each.

  • 02

    If I connect Scale Prediction Model to Claude, can I use the same connection in ChatGPT or Gemini later?

    Yes, and that's the point: the connection is yours, not Claude's. You paste the same link in any AI you use, and there's nothing new to set up or pay again. Connect a new AI and Scale Prediction Model is already there.

  • 03

    Do I need to hand my Scale Prediction Model password to Claude?

    Never. You sign in once at Vinkius, and we keep your logins encrypted and away from your AI. Claude only ever sees the link, and you can remove it whenever you want.

  • 04

    What can I actually ask Claude to do with Scale Prediction Model?

    Whatever the Connector covers: check data, run actions and bring answers back into the chat. The Connector page lists every capability your AI gains, with real examples you can copy.

  • 05

    Claude doesn't show the Connector. What do I check?

    Make sure the link was pasted exactly as copied and that the Connector is active in your Vinkius account, then reopen the connectors list in Claude. A deactivated Connector stops appearing in new chats.

  • 06

    Can I remove the access later?

    Anytime. Remove the connector under Customize and Connectors in Claude and it's out of your chats. Your Vinkius account keeps the connection and its history either way, ready for the next AI.

  • More questions about Scale Prediction Model? The Connector page answers them. See everything the Scale Prediction Model Connector can do

About the Connector

What Scale Prediction Model adds to your AI.

Once you connect it, your AI gains 4 capabilities: the exact actions it can take in Scale Prediction Model when you ask. The Connector page lists every one of them in detail, alongside the latency we measure in production and prompts worth trying first.

See everything the Scale Prediction Model Connector can do