GenPark Vector Embedding Cache Deduplication Sentinel
LocalAbout GenPark Vector Embedding Cache Deduplication Sentinel
A Python MCP server for semantic deduplication of high-dimensional vector embeddings using SimHash and LRU cache simulation. The README gives its installation configuration but does not detail inputs or operations.
Key features
- 01Semantic SimHash deduplication
- 02High-dimensional vector embeddings
- 03LRU cache simulation
- 04Python standard-library implementation
Use cases
- 01Simulating an embedding cache with LRU behavior
- 02Checking semantic deduplication approaches
MCP support
Runs as an MCP server launched with Python and can be configured in Claude Desktop or Cursor. The README does not specify the tools or resources it exposes.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEgenpark-vector-embedding-cache-deduplication-sentinel-skill
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.
Comments
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