genpark-levenshtein-damerau-fuzzy-matcher-skill

mcp
Guvenlik Denetimi
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SUMMARY

Damerau-Levenshtein edit distance metric with transposition detection and fuzzy string candidate ranker.

README.md

genpark-levenshtein-damerau-fuzzy-matcher-skill

Damerau-Levenshtein edit distance metric with transposition detection and fuzzy string candidate ranker.

Part of the GenPark AI Agent Skills Matrix. Production-ready, zero external dependencies, native Python 3.9+ standard library.

Architecture

flowchart TD
    A[Text Input Corpus] --> B[Tokenization & Subword Extraction]
    B --> C[Vector & Similarity Kernels]
    C --> D[Ranked / Segmented Output]
    D --> E[MCP Protocol Endpoint]

Features

  • Zero Third-Party Dependencies: Pure Python standard library (collections, re, math).
  • High-Performance NLP: Subword BPE merges, Okapi BM25 ranking, and Damerau-Levenshtein metrics.
  • Native MCP Protocol Support: Integrated JSON-RPC 2.0 stdio server ready for Claude Desktop, Cursor, and Windsurf.

Installation

pip install genpark-levenshtein-damerau-fuzzy-matcher-skill

Or clone directly:

git clone https://github.com/alphaparkinc/genpark-levenshtein-damerau-fuzzy-matcher-skill.git
cd genpark-levenshtein-damerau-fuzzy-matcher-skill
python example_usage.py

Quick Start

from client import *
# Refer to example_usage.py for end-to-end execution

Model Context Protocol (MCP) Setup

Add to your claude_desktop_config.json or cursor.json:

{
  "mcpServers": {
    "genpark-levenshtein-damerau-fuzzy-matcher-skill": {
      "command": "python",
      "args": ["-m", "genpark-levenshtein-damerau-fuzzy-matcher-skill.mcp_server"]
    }
  }
}

License

MIT License. Copyright (c) 2026 AlphaPark Inc. & Alpha-Park.

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