Claude and other AIs

How to set up AI Output Quality Metrics in Claude and other AIs

Set up in seconds, once. From then on, AI Output Quality Metrics 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 AI Output Quality Metrics 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

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics link as the remote MCP server URL.
  3. 3Click Add and start a new chat. Ask for something real: AI Output Quality Metrics is now part of your Claude.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

ChatGPT

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics 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: AI Output Quality Metrics is now part of your ChatGPT.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Gemini

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics to Gemini

About a minute, right in your terminal

  1. 1Open the Gemini CLI in your terminal.
  2. 2Run: gemini mcp add --transport http AI Output Quality Metrics <your link>. Your AI Output Quality Metrics link above is the HTTP URL.
  3. 3Run /mcp and confirm the status shows CONNECTED. AI Output Quality Metrics is now part of your Gemini.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Perplexity

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics 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. AI Output Quality Metrics is now part of your Perplexity.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Grok

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics link as the remote MCP server URL.
  3. 3Save and enable it, finish the browser authorization if prompted, and ask Grok something real. AI Output Quality Metrics is now part of your Grok.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Microsoft Copilot

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics link as the server URL with HTTP transport.
  3. 3Confirm the server appears in your MCP list, then ask Copilot something real. AI Output Quality Metrics is now part of your Copilot.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Cursor

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics with the url field set to your link. The link above is the URL.
  3. 3Save, enable the server, and ask something real. AI Output Quality Metrics is now part of Cursor.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

VS Code

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics with type http and your link as the url. The link above is the URL.
  3. 3Save and ask something real in Copilot Chat. AI Output Quality Metrics is now part of VS Code.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Windsurf

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics with the serverUrl field set to your link. The link above is the URL.
  3. 3Save and ask something real. AI Output Quality Metrics is now part of Windsurf.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

JetBrains

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics to JetBrains

About a minute, in Settings

  1. 1Go to Settings, Tools, AI Assistant, Model Context Protocol (MCP).
  2. 2Click Add and add AI Output Quality Metrics 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. AI Output Quality Metrics is now part of your IDE.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Cline

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics 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. AI Output Quality Metrics is now part of Cline.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

LangChain

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics link: MCPAdapter("<your link>"). The link above is the URL.
  3. 3Call list_tools and pass the tools to your agent. AI Output Quality Metrics is now part of your LangChain agent.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Vercel AI SDK

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics 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. AI Output Quality Metrics is now part of your AI SDK app.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Lovable

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics link as the Server URL. The link above is the URL.
  3. 3Choose No authentication and click Add server, then ask Lovable something real. AI Output Quality Metrics is now part of Lovable.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Z.ai

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics 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. AI Output Quality Metrics is now part of Z.ai.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Raycast

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics 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. AI Output Quality Metrics is now part of Raycast.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Qwen Code

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics to Qwen Code

About a minute, in your terminal

  1. 1Run: qwen mcp add --transport http AI Output Quality Metrics <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. AI Output Quality Metrics is now part of Qwen Code.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Kimi Code

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics 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 AI Output Quality Metrics with your link in the url field. The link above is the URL.
  3. 3Run /mcp to confirm the status, then ask something real. AI Output Quality Metrics is now part of Kimi Code.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Le Chat

AI Output Quality Metrics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

Connecting AI Output Quality Metrics to Le Chat

About a minute, in Connectors

  1. 1In Le Chat, open Connectors and choose to add a custom connector.
  2. 2Paste your AI Output Quality Metrics link as the remote MCP server URL. The link above is the URL.
  3. 3Save and authorize, then ask something real. AI Output Quality Metrics is now part of Le Chat.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-output-quality-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp"
    }
  }
}

Claude and other AIs + AI Output Quality Metrics

One chat. Your AI Output Quality Metrics, 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 AI Output Quality Metrics Connector. Once yours is connected, they work in your chats.

The full capability set, the prompts and the observed latency live on the AI Output Quality Metrics Connector page.

Mission Control

See everything your agents do in AI Output Quality Metrics.

When your agents run a tool in AI Output Quality Metrics, 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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Total in this period
Avg Latency
0
API 88ms · Overhead 54ms
Vinkius Reliability
0
Agent 280 · Upstream 47 · Vinkius 15
Tokens
0
AI tokens processed
DLP Protected
0
Sensitive data redacted
Cost Saved
0
FinOps truncations applied

AI Agents Activities

last 30 days
30d agotoday

Request Volume & Latency

requests latency

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

What sets us apart

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

Connecting AI Output Quality Metrics to your AI is step one. But an open line between your agents and AI Output Quality Metrics 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 AI Output Quality Metrics is recorded and signed, so any change to the history becomes detectable.

02

Automatic Key Rotation

We rotate security keys every 24 hours. Your AI Output Quality Metrics 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 AI Output Quality Metrics actions never surprise you.

04

Isolated Sandbox

Every execution through AI Output Quality Metrics 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 AI Output Quality Metrics 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 AI Output Quality Metrics.

08

Credential Validation

We test your AI Output Quality Metrics 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 AI Output Quality Metrics connection runs on. Read how our infrastructure protects everything your agents do, end to end.

Inside Vinkius

Get AI Output Quality Metrics ready for your AI. It's easy.

You choose AI Output Quality Metrics from the Vinkius Catalog and get one connection link. That's it.

  1. You choose AI Output Quality Metrics

    You find AI Output Quality Metrics in the Catalog and install the Connector with one click.

    AI Output Quality Metrics

    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 AI Output Quality Metrics is live everywhere in one move.

    Token generated successfully

    MCP Connection URL

    https://edge.vinkius.com/vk_preview_dxYjaLZjJBEchfmzed34pkMXEQbtRV6Vu6JCBElQ/mcp

    Connection Token

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

Set it up once. Use AI Output Quality Metrics 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 AI Output Quality Metrics 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 AI Output Quality Metrics is already there.

  • 03

    Do I need to hand my AI Output Quality Metrics 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 AI Output Quality Metrics?

    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 AI Output Quality Metrics? The Connector page answers them. See everything the AI Output Quality Metrics Connector can do

About the Connector

What AI Output Quality Metrics adds to your AI.

Once you connect it, your AI gains 4 capabilities: the exact actions it can take in AI Output Quality Metrics 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 AI Output Quality Metrics Connector can do