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Connect Token Count Estimator to ChatGPT, Claude and Gemini

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 your input size and context limits.

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 Token Count Estimator.

  1. 01

    Analyze text complexity

    This capability evaluates the structural characteristics of your text. It prepares the data for specific density calculations like code or URL detection.

  2. 02

    Estimate token usage

    This capability provides a full breakdown of your estimated token count. It also shows how much capacity remains in your current context window.

  3. 03

    Get model ratios

    This capability retrieves hardcoded character-to-token ratios. It uses the specific model and language you request to ensure accuracy.

Real work

What teams actually run

01

Large Document Processing

Check if a massive PDF or text file will fit into your model's context window before you upload it.

02

Codebase Analysis

Determine the token impact of adding specific code files to your agent's context.

03

Cost Prediction

Get a breakdown of token usage to estimate the cost of long-running tasks.

04

Multi-language Optimization

Use specific character-to-token ratios to manage non-English inputs accurately.

One connector, every AI

Token Count 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 Token Count 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

885ms average. Fast in production.

Token Count Estimator is checked daily against the live service.

Daily averagePeak 1107ms
Oct 3Today
Fastest day
814ms
Slowest day
1107ms
14-day trend
Improving-23%

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

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

Token Count Estimator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_WRXaDwN8B6yoUlZJBByOQGcYopoEFZ1yRxVUQweP/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 — Token Count Estimator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "token-count-estimator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_WRXaDwN8B6yoUlZJBByOQGcYopoEFZ1yRxVUQweP/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 Token Count Estimator in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Token Count Estimator owners hand off.

This is for developers and prompt engineers who need to manage large-scale inputs for LLMs.

  • 01

    Prompt Engineers

    They use it to optimize long prompts to stay within context limits.

  • 02

    AI Developers

    They use it to predict token costs and manage input density for applications.

  • 03

    Data Scientists

    They use it to analyze the structural complexity of text datasets before processing.

FAQ

Questions Token Count Estimator owners ask.

  • 01

    How accurate is the token estimation?

    The estimation is deterministic and uses model-specific linguistic ratios and structural density analysis to provide precise counts.

  • 02

    Which AI clients can use this MCP?

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

  • 03

    Does it support different languages?

    Yes, it retrieves hardcoded character-to-token ratios for specific languages to ensure accuracy across different linguistic structures.

  • 04

    Can it detect code in my prompts?

    Yes, the analysis capability evaluates structural characteristics to detect code and URL density.

  • 05

    How do I know if I am hitting the context limit?

    The MCP provides a breakdown of remaining capacity and warns you when you are approaching the limit.

  • 06

    How accurate are these token estimates?

    The estimates use deterministic character-based heuristics. For English, we provide a ±10% confidence interval, while mixed languages use a ±15% interval.

  • 07

    Which models are supported?

    The server supports GPT-4, Claude, Llama, and Gemma through specific character-to-token ratios.

  • 08

    Can I detect if my text is too long for the model?

    Yes, the estimate_token_usage capability includes an isOverCapacityWarning flag that triggers when you exceed 90% of the specified context window.

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