Tool Output Entropy Sanitizer

Tool Output Entropy Sanitizer MCP Connector for Claude

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Detects and redacts high-entropy strings like API keys from tool outputs.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner

The Tool Output Entropy Sanitizer is a security-focused MCP server designed to prevent sensitive data leakage into LLM context windows. By implementing a sliding-window analysis, the sanitize_text_output tool scans input strings for segments that exceed an entropy threshold of 4.5. It uses deterministic character frequency analysis to identify high-entropy patterns characteristic of API keys, passwords, or encoded payloads. The server also provides evaluate_segment_entropy to audit specific substrings and verify_window_bounds to ensure window sizes remain within the operational bounds of 16 to 64 characters. When a secret is detected, it is replaced with a structured redaction pattern like [REDACTED_HIGH_ENTROPY:length], preserving the structural context for the AI while protecting sensitive information.

entropyredactionsecuritysanitizationprivacy

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

sanitize_text_output

Returns the sanitized text and metadata about redactions. Sanitizes text by redacting high-entropy segments

verify_window_bounds

Ensures a proposed window size adheres to constraints

evaluate_segment_entropy

Input must be at least 16 characters long. Audits the randomness of a specific piece of text

See how to talk to your AI agent using Tool Output Entropy Sanitizer.

Sanitize this string: 'My API key is ABC123XYZ789! and my name is John'.

The sanitized text is: 'My API key is [REDACT_HIGH_ENTROPY:15] and my name is John'. Redacted count: 1.

What is the entropy score for 'password1234567890abcde'?

The entropy score for the segment is 3.8, which is below the high-entropy threshold.

Is a window size of 10 valid for entropy analysis?

No, the window size is invalid. The `verify_window_bounds` tool indicates it must be between 16 and 64 characters.

The server uses Shannon entropy calculation. If a window of text has an entropy score above 4.5, it is flagged as high-risk and redacted.

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