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Connect Performance Regression Detector 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. Stop unexpected latency spikes and cost increases in your agent workflows.

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 · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through Performance Regression Detector.

  1. 01

    Predict failure horizon

    This capability forecasts when your performance will hit a critical limit based on current degradation trends.

  2. 02

    Analyze execution anomalies

    This capability identifies specific execution instances that deviate significantly from your historical performance baseline.

  3. 03

    Calculate performance trend

    This capability determines if your system is experiencing a systemic slowdown over time.

Real work

What teams actually run

01

Agent Loop Monitoring

Watch for slowdowns in long-running agentic reasoning loops.

02

Deployment Validation

Check if a new model or prompt version causes a regression in execution speed.

03

Budget Protection

Identify when increased latency will lead to higher compute costs.

04

SLA Compliance

Predict when execution times will violate your defined latency limits.

One connector, every AI

Performance Regression Detector 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 Performance Regression Detector 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

888ms average. Fast in production.

Performance Regression Detector is checked daily against the live service.

Daily averagePeak 1035ms
Oct 3Today
Fastest day
681ms
Slowest day
1035ms
14-day trend
Improving-14%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 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 Performance Regression Detector, so you can see the experience inside your AI.

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

Performance Regression Detector Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_Mrc7VLVZnW2CJ3Vp0BfcGsW4A6xTf6bdZnQTBTMV/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 — Performance Regression Detector capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "performance-regression-detector-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_Mrc7VLVZnW2CJ3Vp0BfcGsW4A6xTf6bdZnQTBTMV/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 Performance Regression Detector in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Performance Regression Detector owners hand off.

This MCP is built for engineers managing autonomous agent workflows that require predictable execution speeds.

  • 01

    AI Engineers

    They use this to monitor agentic loops and prevent latency-driven failures.

  • 02

    MLOps Engineers

    They hand off execution logs to the agent to identify systemic performance drifts.

  • 03

    Backend Developers

    They use this to ensure new agent deployments don't introduce regressions.

FAQ

Questions Performance Regression Detector owners ask.

  • 01

    How does this MCP detect performance issues?

    It uses deterministic statistical calculations to find anomalies and trends in execution times.

  • 02

    Can I use this with Claude or Cursor?

    Yes, you can connect this MCP to any MCP-compatible client including Claude, Cursor, and Windsurf.

  • 03

    What does the failure horizon capability do?

    It forecasts when your performance will reach a critical limit based on the current rate of degradation.

  • 04

    Does this help with cost management?

    Yes, by detecting regressions in execution time, it helps prevent the cost spikes associated with slower agent runs.

  • 05

    How is an anomaly defined?

    An anomaly is an execution instance that deviates significantly from your historical performance data.

  • 06

    How does the capability identify a regression?

    An execution is flagged as a regression if its duration exceeds the baseline median plus two times the baseline standard deviation.

  • 07

    Can I predict when my agent will hit a latency limit?

    Yes, by using predict_failure_horizon, you can estimate the number of execution cycles remaining before a critical latency limit is breached based on current trends.

  • 08

    What is the purpose of the trend analysis?

    The calculate_performance_trend capability uses linear regression to determine if the system is experiencing a systemic slowdown over time.

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