An astronaut overseeing a futuristic data hub
Download PDFMarkdown Version

Connect Context Window Token Estimator to ChatGPT and Claude

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 guessing if your prompt fits the context limit.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

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 Context Window Token Estimator.

  1. 01

    Analyze context distribution

    This capability breaks down your agent's full payload into its individual parts to check against capacity limits. It shows you exactly how much space each component occupies.

  2. 02

    Estimate payload tokens

    This capability calculates the estimated token count for specific parts of your input. Use it to measure individual components like system prompts or user queries.

  3. 03

    Get limit tier info

    This capability identifies the closest standard model capacity tier for a specific token count. It helps you map your data to common window sizes.

Real work

What teams actually run

01

RAG Optimization

Check if the retrieved documents from your vector database will fit in the current context window.

02

System Prompt Tuning

Measure how much space your complex system instructions are taking up.

03

Multi-turn Conversation Management

Monitor the growing token count as a conversation progresses through multiple turns.

04

Model Tier Planning

Determine if your current payload requires moving to a higher capacity model tier.

One connector, every AI

Context Window Token Estimator 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 Context Window Token Estimator 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

835ms average. Fast in production.

Context Window Token Estimator is checked daily against the live service.

Daily averagePeak 1177ms
Oct 3Today
Fastest day
699ms
Slowest day
1177ms
14-day trend
Improving-15%

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 Context Window Token Estimator, so you can see the experience inside your AI.

It does not authenticate your account with Context Window Token Estimator. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Context Window Token Estimator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_JSrmRV3GM3NOBDbS6k7ZafkvGpk7uNiLmaM4sSsQ/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 — Context Window Token Estimator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "context-window-token-estimator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_JSrmRV3GM3NOBDbS6k7ZafkvGpk7uNiLmaM4sSsQ/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 Context Window Token Estimator in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Context Window Token Estimator owners hand off.

This is for developers and prompt engineers who build complex agentic workflows that rely on large context windows.

  • 01

    AI Engineers

    They use it to ensure RAG payloads don't exceed model limits.

  • 02

    Prompt Engineers

    They use it to optimize the size of system instructions and few-shot examples.

  • 03

    LLM Developers

    They use it to manage token consumption across different model tiers.

FAQ

Questions Context Window Token Estimator owners ask.

  • 01

    What does this MCP actually do?

    It provides precise token estimation and payload distribution analysis for your AI agent's context window.

  • 02

    Which AI clients can use this MCP?

    You can use it with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

  • 03

    How does it handle different context limits?

    It can check your payload against specific limits such as 8k, 16k, 32k, or 128k.

  • 04

    Is the token count exact?

    The MCP uses deterministic heuristics to provide precise token estimations for your inputs.

  • 05

    Do I need to host this myself?

    No, Vinkius hosts and manages the MCP for you, so it is ready to use immediately after connection.

  • 06

    How are tokens calculated?

    The server uses a combination of character-based density (roughly 4 characters per token) and word-boundary splitting to provide a deterministic estimate.

  • 07

    Can I check if my prompt will exceed the model limit?

    Yes, by using analyze_context_distribution, you can compare your total token count against standard tiers like 8k, 16k, 32k, or 128k.

  • 08

    What components can be analyzed?

    You can analyze the system prompt, few-shot examples, RAG context, and the user query to see the full distribution.

Explore

More in Utilities

Suggestions

Connect Context Window Token Estimator to Claude, Cursor, ChatGPT & more