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GenPark Vector Embedding Cache Deduplication Sentinel

High-dimensional vector embedding semantic SimHash deduplication sentinel with LRU cache simulation

AI & MLPythonv1.0.1
View on GitHub

genpark-vector-embedding-cache-deduplication-sentinel-skill

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High-dimensional vector embedding semantic SimHash deduplication sentinel with LRU cache simulation

Quick Installation & MCP Integration

Add to your Claude Desktop or Cursor configuration:

{
  "mcpServers": {
    "genpark-vector-embedding-cache-deduplication-sentinel-skill": {
      "command": "python",
      "args": ["mcp_server.py"]
    }
  }
}

Zero Dependencies

Implemented entirely in Python 3 standard library.

Setup from the maintainer

This listing does not have a supported local package template. Use the maintainer’s documentation for its hosted endpoint, authentication, and client-specific setup. No install command has been inferred.

Package

https://github.com/Alpha-Park/genpark-vector-embedding-cache-deduplication-sentinel-skill/releases/download/v1.0.1/genpark-vector-embedding-cache-deduplication-sentinel-skill.mcpbother

Compatible MCP Clients

GenPark Vector Embedding Cache Deduplication Sentinel works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

  • Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.
  • Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.
  • VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.
  • Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.
  • Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

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