MCP For Claude Marketplace
MinHash Text Deduplicator

MinHash Text Deduplicator MCP Connector for Claude

A+

Detect near-duplicate texts using MinHash signatures and Jaccard similarity.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides tools to identify redundant content within large text collections. By using shingling and deterministic MinHash signatures, it estimates Jaccard similarity to find near-duplicates. Use compute_similarity_matrix to see how all texts relate, identify_duplicate_clusters to group similar items, or check_is_duplicate to verify if a specific text already exists in your library.

minhashjaccard-similaritydeduplicationtext-analysisshingling

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

check_is_duplicate

Performs a binary check to determine if a new piece of text is a near-duplicate of any existing text

compute_similarity_matrix

Calculates the estimated Jaccard similarity between all provided text entries

identify_duplicate_clusters

Groups texts into distinct sets of near-duplicates based on a specific similarity requirement

See how to talk to your AI agent using MinHash Text Deduplicator.

Find all groups of duplicate texts in this list: ['Hello world', 'Hello world!', 'Goodbye moon', 'Goodbye moon!'] with a threshold of 0.8.

[[0, 1], [2, 3]]

Is 'The quick brown fox' a duplicate of ['The quick brown fox jumps over the lazy dog'] with a threshold of 0.5?

No, the similarity is below the threshold.

Show me the similarity matrix for these three sentences: ['A', 'B', 'C'].

[[1.0, 0.0, 0.0], [0.0, 1.0, 0.0], [0.0, 0.0, 1.0]]

It uses MinHash signatures to estimate the Jaccard similarity between sets of shingles, providing a score between 0.0 and 1.0.

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