GenPark Vector Embedding Cache Deduplication Sentinel

Local Python MCP server that simulates semantic SimHash deduplication of high-dimensional vector embeddings with an LRU cache.

What you can do

• Deduplicate high-dimensional vector embeddings using semantic SimHash comparison
• Simulate an LRU cache for embedding lookups and reuse
• The README lists no individual tools, so exact operations are not documented
• Runs as a small Python 3 standard-library script with no third-party dependencies

When to use it

Worth trying when you want an assistant to experiment with near-duplicate detection across embeddings or to model cache behavior for embedding pipelines, without adding external services.

Requirements

A local Python 3 runtime; the README's example configuration launches mcp_server.py with the python command. No API keys, environment variables or headers are declared. Desktop client only (Claude Desktop or Cursor style configuration).