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Prefix Cache Savings Calculator

Prefix Cache Savings Calculator MCP Connector for Claude

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Calculate exact token savings from LLM prefix caching.

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

This MCP server provides tools to analyze how much token usage can be reduced by using prefix caching. By identifying the longest common prefix across a set of prompts, it calculates exact savings in tokens and percentage efficiency. Use analyze_prefix_savings to get detailed metrics or get_cache_efficiency_metrics for a high-level recommendation on caching potential.

prefix-cachingtoken-optimizationllm-efficiencyprompt-engineeringcost-reduction

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

analyze_prefix_savings

Calculates the exact cache savings resulting from a shared prefix across a provided set of prompts

find_longest_common_substring

Identifies the specific character sequence shared by the prompts to validate the prefix

get_cache_efficiency_metrics

Provides a high-level summary of whether a set of prompts is a good candidate for prefix caching

See how to talk to your AI agent using Prefix Cache Savings Calculator.

Calculate the savings for these prompts: ['System: Act as a tutor. User: Hello', 'System: Act as a tutor. User: How are you?', 'System: Act as a tutor. User: Help me with math.']

The common prefix is 'System: Act as a tutor. User: '. The total tokens saved is 32 tokens, resulting in a 45% savings efficiency.

Is this set of prompts efficient for caching? ['Prompt A', 'Prompt B', 'Prompt C']

No significant savings detected for this set of prompts.

Find the common prefix for: ['abcde', 'abcdx', 'abcdy']

The common prefix is 'abcd'.

The tool identifies the common prefix shared by all prompts and estimates tokens using a 4-character-per-token ratio. It then calculates savings by multiplying the prefix tokens by the number of additional prompts that benefit from the cache.

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