MCP For Claude Marketplace
Prompt Length Classifier

Prompt Length Classifier MCP Connector for Claude

A+

Estimate token usage and context window saturation.

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

This MCP server provides deterministic tools to calculate token consumption and context window utilization. Use classify_prompt_usage to get a full breakdown of estimated tokens, usage percentage, and available headroom. Use validate_window_capacity to ensure your prompt and expected response fit safely within a model's limits. It is designed to help developers and agents manage context more effectively.

tokenscontext-windowllmestimationprompt-engineering

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

classify_prompt_usage

Calculates all metrics regarding token estimation, context saturation, and available headroom for a given text and context window

validate_window_capacity

Verifies if a specific amount of text can fit within a specific context window while still leaving room for the required output reservation and safety margin

get_context_tier_definitions

Provides the logic-based definitions for the qualitative length categories

See how to talk to your AI agent using Prompt Length Classifier.

How much of my 8192 context window will this text use: 'Hello world'?

The text 'Hello world' uses approximately 3 tokens, which is 0.03% of an 8192 token window.

Will a 5000 token prompt fit in a 4096 token window?

No, a 5000 token prompt exceeds the 4096 token capacity of the window.

Calculate the usage for a 1000 character text in a 32768 window.

The estimated tokens are 250, representing 0.76% of the 32768 context window.

Tokens are estimated by dividing the total character count of the input text by four.

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