MCP For Claude Marketplace
AI Token Counter

AI Token Counter MCP Connector for Claude

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Give AI Agents self-awareness of context limits. Count exact OpenAI/Claude tokens local to prevent fatal API truncation errors.

1 tools Official Updated Jun 28, 2026 Official Vinkius Partner
More Details Connect to Claude

When a RAG Agent fetches 10 documents to summarize, it blindly sends them to the LLM API. If the payload exceeds the context window (e.g., 128k tokens), the API crashes, destroying the pipeline. LLMs cannot count their own tokens before sending a prompt. This MCP solves that perfectly.

The Superpowers

  • Token Math: Uses the exact cl100k_base encoding algorithm local to tell the Agent exactly how many tokens a payload contains.
  • Self-Aware Agents: Allows Agents to do math and chunk their own massive datasets safely before hitting external API limits.
tokenizationcontext-windowllm-optimizationcost-managementapi-limitsencoding

1 tools expose this connector's capabilities to your AI agent.

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

See how to talk to your AI agent using AI Token Counter.

Tell me how many tokens are in this huge block of JSON data.

Token Count Result: There are 8540 tokens.

Count the tokens in this article so I know if I can fit it into my next prompt.

Token Count Result: The article has 2300 tokens.

I need the exact token count for this transcript snippet.

Token Count Result: Successfully counted.

It uses the `cl100k_base` encoding, which is the exact algorithm used by GPT-3.5, GPT-4, and most Claude models.

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