MCP For Claude Marketplace
Claude Verbosity Optimizer

Claude Verbosity Optimizer MCP Connector for Claude

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A deterministic engine to detect and compress verbose LLM outputs to preserve context window budget.

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

The Claude Verbosity Optimizer is a deterministic toolset designed to prevent context bloat in AI conversations. It identifies redundant reasoning, repetitive descriptions, and narrative filler using mathematical rules like Jaccard similarity. By using compress_text, users can automatically apply rules such as redundant sentence removal, file list collapsing, and code block sanitization to stay within strict token limits. It provides precise control over context management without the unpredictability of LLM-based summarization.

llmtoken-optimizationcontext-windowdeterministicverbosity-control

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

analyze_verbosity

Assess the current state of a text block and determine how much waste exists relative to a specific budget

compress_text

Execute deterministic reduction rules on a given text block to meet a token budget

get_optimization_report

Provide a structured overview of the optimization effectiveness for auditing purposes

See how to talk to your AI agent using Claude Verbosity Optimizer.

Analyze this response for verbosity: 'I will now proceed to analyze the code. I am analyzing the code. The code is being analyzed by me.' with a budget of 50 tokens.

The `analyze_verbosity` tool indicates high redundancy due to the repetitive nature of the sentences.

Compress this text to 20 tokens: 'The user requested a file list. Modified file1.ts, modified file2.ts, modified file3.ts, modified file4.ts.'

Modified 4 files in the project.

How can I see how much space I saved after compression?

You can use the `get_optimization_report` tool to compare the original and optimized text and see the exact compression ratio.

Unlike LLM summarization, this tool uses mathematical rules like Jaccard similarity and structural patterns to remove text, ensuring the technical meaning remains unchanged.

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