genpark-contextual-memory-pruning-importance-attributor-skill MCP Server
alphaparkinc/genpark-contextual-memory-pruning-importance-attributor-skill
[](https://agentrank-ai.com/tool/alphaparkinc--genpark-contextual-memory-pruning-importance-attributor-skill/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) Autonomous Long-Horizon Agentic Memory Pruning & Importance Attributor. Evaluates multi-turn episodic memory buffers, calculates multi-factor salience scores (recency decay, user priority pinning, emotional valence, and entity graph connectivity), and deterministically prunes low-utility noise to respect model context limits.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
alphaparkinc/genpark-contextual-memory-pruning-importance-attributor-skill is a Python tool licensed under MIT. Autonomous Long-Horizon Agentic Memory Pruning & Importance Attributor. Evaluates multi-turn episodic memory buffers, calculates multi-factor salience scores (recency decay, user priority pinning, emotional valence, and entity graph connectivity), and deterministically prunes low-utility noise to respect model context limits.
Ranked #7069 out of 24846 indexed tools.
Ecosystem
Score Breakdown
7 stars → early stage
Last commit 12d ago → recently updated
No issues filed → no history to score
0 contributors → solo project
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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