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Context Window Compression Calculator

Context Window Compression Calculator MCP Connector for Claude

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Mathematically model token reduction strategies and quality trade-offs.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides precise mathematical modeling for LLM context window management. It allows AI agents to calculate optimal compression strategies by balancing token reduction against semantic integrity. Use calculate_compression_strategy to find the best mix of techniques like summarization or pruning to hit a target token count. You can also use simulate_cascading_compression to model sequential stages of reduction, or evaluate_technique_efficiency to compare how different methods perform under specific constraints.

tokenscompressioncontext-windowllm-optimizationdata-science

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

evaluate_technique_efficiency

Provide a comparison of how different techniques perform against specific target constraints

simulate_cascading_compression

Model the outcome of applying multiple compression stages in a specific sequence

calculate_compression_strategy

Determine the most efficient way to reach a specific target token count using a specific set of techniques

See how to talk to your AI agent using Context Window Compression Calculator.

I have 10,000 tokens and I need to get down to 1,000. What is the best strategy using summarization and pruning?

The optimal strategy to reach 1,000 tokens from 10,000 is a mix of summarization and pruning, resulting in a compression ratio of 10:1 with an estimated quality loss of 15%.

Compare the efficiency of deduplication versus abstraction for 5,000 tokens at a 5:1 ratio.

At a 5:1 ratio, deduplication is not sufficient as its max ratio is 3:1. Abstraction can achieve this ratio with an estimated quality loss of 25%.

Simulate a two-step compression: first deduplication, then summarization on 2,000 tokens.

After deduplication and subsequent summarization, the final token count is 250, with a cumulative quality loss of 22%.

You can use the `calculate_compression_strategy` tool. Provide your original token count, your target token count, and the techniques you want to allow, and it will return the optimal mix to minimize quality loss.

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