MCP For Claude Marketplace
Context Window Token Estimator

Context Window Token Estimator MCP Connector for Claude

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Calculate exact token counts and payload distribution for AI agent context windows.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides precise token estimation for AI agents. It uses deterministic heuristics to calculate token counts for system prompts, few-shot examples, RAG context, and user queries. Use analyze_context_distribution to check if your total payload fits within specific model limits (8k, 16k, 32k, or 128k) and to visualize how much space each component occupies.

tokenscontext-windowllmestimationpayload

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

analyze_context_distribution

Breaks down a complete agent payload into its constituent parts and checks against capacity

estimate_payload_tokens

Calculates the estimated token count for individual components of an agent's input

get_limit_tier_info

Identifies the closest standard model capacity tier for a given token count

See how to talk to your AI agent using Context Window Token Estimator.

How many tokens are in this text: 'Hello world, this is a test.'?

The estimated token count for the text is 7.

Analyze my context: System: 'You are a helpful assistant'. Query: 'What is the weather?' with a 16k limit.

Total tokens: 12. Utilization: 0.07%. Status: Within limit.

What is the next standard model tier for 10,000 tokens?

The next standard tier is 16,384 tokens.

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

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