Skip to main content
Glama
Alpha-Park

genpark-contextual-memory-pruning-importance-attributor-skill

Official
by Alpha-Park

Related Servers

Alternatives to genpark-contextual-memory-pruning-importance-attributor-skill

No user-submitted related servers found.

    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to calculate multi-factor salience scores for episodic memories using recency decay, user priority pinning, emotional valence, and entity graph connectivity, then deterministically prune low-utility entries to respect model context limits.
      7
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables agents to maintain multi-tier memory across working scratchpad, dialogue buffer, and episodic stores with recency decay. Supports hybrid BM25/vector retrieval, rank fusion, graph expansion, and context reordering for optimized MCP-based memory and RAG workflows.
      7
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Scores AI agent context entries for relevance using Jev and prunes or summarizes those that are no longer useful, helping MCP hosts reduce token usage and context bloat.
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI agents to combine ambient multimodal perception, continuous episodic memory, and recency-decay context briefing for fast deterministic decisions and safe tool routing. It integrates with MCP clients to reduce unnecessary frontier LLM calls while enforcing token budgets and local-first memory retention.
      7
      MIT
    • A
      license
      A
      quality
      B
      maintenance
      Enables AI agents to maintain long-term, cross-session memory by extracting facts, reconciling state conflicts, and retrieving relevant memories via vector search.
      4
      MIT

    Maintenance

    ActivityMaintained
    ResponsivenessNo issues