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genpark-agent-semantic-cache-query-matcher-skill

mcp
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README.md

Semantic Cache Query Matcher Skill for Autonomous Agents

MCP Compatible
Python 3.9+
License: MIT
Zero External Dependencies

High-performance in-memory semantic cache designed to slash LLM inference costs and latency by caching query-response pairs with fuzzy cosine term-vector matching.

Key Features

  • Cosine Term Vector Matching: Zero external vector database; computes term-frequency vector similarity in pure Python.
  • Configurable Similarity Threshold: Tunable confidence threshold (e.g. 0.75 - 0.95) to prevent false-positive matches.
  • Hit Rate Telemetry: Tracks hits, misses, and saved token estimations.

MCP Server Integration

python mcp_server.py

Available MCP Tools

  • cache_set: Store query and generated response.
  • cache_get: Lookup semantic match for an incoming prompt.
  • cache_stats: Return total entries, hits, and cache utilization.

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