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Connect Claude Reasoning Effort Calibrator 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. Match task complexity to the right reasoning effort.

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 Claude Reasoning Effort Calibrator.

  1. 01

    Calculate reasoning needs

    This capability determines the required reasoning effort and predicts how long the task will take based on the provided context.

  2. 02

    Get latency config

    This capability retrieves the latency coefficients used to calculate time estimates.

  3. 03

    Get effort mapping

    Use this to see the specific complexity thresholds that trigger different effort levels.

Real work

What teams actually run

01

Code Refactoring

Your agent calculates XHIGH effort when it needs to change core architectural components.

02

Bug Fixing

The MCP determines if a bug requires deep reasoning or just a simple logic fix.

03

Automated Testing

It predicts the time needed to generate tests based on the number of files involved.

04

Dependency Analysis

The capability uses dependency depth to scale the required reasoning effort.

One connector, every AI

Claude Reasoning Effort Calibrator 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 Claude Reasoning Effort Calibrator 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

868ms average. Fast in production.

Claude Reasoning Effort Calibrator is checked daily against the live service.

Daily averagePeak 986ms
Oct 3Today
Fastest day
655ms
Slowest day
986ms
14-day trend
Improving-10%

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 Claude Reasoning Effort Calibrator, so you can see the experience inside your AI.

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

Claude Reasoning Effort Calibrator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_i0GimZLBokv2HoPddCNJ0dJc8H3P6YfVrcAquxv7/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 — Claude Reasoning Effort Calibrator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "claude-reasoning-effort-calibrator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_i0GimZLBokv2HoPddCNJ0dJc8H3P6YfVrcAquxv7/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 Claude Reasoning Effort Calibrator in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Claude Reasoning Effort Calibrator owners hand off.

This is built for developers and engineers who want to optimize how their AI agents interact with codebases.

  • 01

    Software Engineers

    They use it to decide how much reasoning power to assign to refactoring or debugging tasks.

  • 02

    AI Agents Developers

    They use it to build more efficient workflows by predicting task latency.

  • 03

    DevOps Engineers

    They use it to manage resource allocation and time expectations for automated tasks.

FAQ

Questions Claude Reasoning Effort Calibrator owners ask.

  • 01

    What effort levels can this MCP provide?

    The MCP provides four distinct levels: LOW, MEDIUM, HIGH, and XHIGH.

  • 02

    How does it decide on the reasoning effort?

    It analyzes task complexity through metrics like file modification volume, dependency depth, and architectural impact.

  • 03

    Can I see the math behind the latency estimates?

    Yes, you can use the get_latency_config capability to retrieve the specific latency coefficients used for estimations.

  • 04

    What determines the complexity score?

    The score is derived from the specific metrics of the task, such as how many files are being changed and how deep the dependencies are.

  • 05

    How do I know the thresholds for each level?

    You can use the get_effort_mapping capability to see the exact boundary values for each effort tier.

  • 06

    How does the complexity score work?

    The score is a weighted sum of four dimensions: file modification volume, dependency depth, architectural impact, and ambiguity level detected in the task description.

  • 07

    What are the available effort levels?

    The system maps scores to LOW, MEDIUM, HIGH, or XHIGH effort levels based on fixed thresholds.

  • 08

    Can I see the latency multipliers?

    Yes, you can use get_latency_config to retrieve the coefficients used for different model types.

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