Download PDFMarkdown Version
ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use GPT Tokenizer with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Keep your complex workflows running without hitting API limits.

Included with plan

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

Complete set · 1 capability

The complete GPT Tokenizer capability set.

These are the exact actions your AI can choose when you ask it to work with GPT Tokenizer.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through GPT Tokenizer.

  1. 01

    Count tokens

    Pass the raw text and receive the exact token count. Use the result to decide whether to chunk, summarize, or send directly. Counts exact LLM tokens (cl100k_base) offline. Prevents RAG agents from exceeding context windows and crashing

Observed, not estimated

1735ms average. Fast in production.

GPT Tokenizer is checked daily against the live service.

Daily averagePeak 1974ms
Aug 20Today
Fastest day
1464ms
Slowest day
1974ms
14-day trend
Stable+1%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 1 capability arrives 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 GPT Tokenizer, so you can see the experience inside your AI.

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

GPT Tokenizer Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_3TlaUrJfXkjzPylHQtgw7qX3SzCKmj8umGecyFc1/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 — GPT Tokenizer capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-token-counter-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_3TlaUrJfXkjzPylHQtgw7qX3SzCKmj8umGecyFc1/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

Who it's for

Built for the work GPT Tokenizer owners hand off.

This MCP is built for developers and prompt engineers who build complex, multi-step AI agents. If your workflow involves summarizing large documents, processing extensive data sets, or building Retrieval Augmented Generation (RAG) pipelines, you need this capability. It gives your agent the necessary math to handle real-world data limits.

  • 01

    AI Developer

    Builds agents that must reliably process inputs of unknown size, preventing runtime API failures.

  • 02

    Prompt Engineer

    Designs prompts that handle massive amounts of context, ensuring the prompt doesn't exceed the model's limit.

  • 03

    Data Scientist

    Needs to pre-process and chunk large data sources before feeding them into an LLM for analysis.

FAQ

Questions GPT Tokenizer owners ask.

  • 01

    Does this count the tokens for all LLMs?

    No, it uses the specific cl100k_base encoding algorithm. This ensures the count matches the tokenization method used by the target LLM API, making the count accurate for your workflow.

  • 02

    Is this better than just guessing the token count?

    Yes. Guessing is unreliable. This MCP provides a precise, local count of the raw text, giving your agent the mathematical certainty it needs to avoid unexpected API failures.

  • 03

    Can my agent use this to save money?

    Absolutely. By knowing the exact token count, your agent can optimize its prompts and chunking strategy, preventing unnecessary API calls and keeping your costs down.

  • 04

    What kind of data can I feed into the token counter?

    You can feed it any raw text, including JSON data, articles, transcripts, or any large block of text your agent needs to analyze.

Explore

More in Productivity

Suggestions