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Related Servers

Alternatives to agentchat-memory

No user-submitted related servers found.

    Related Servers

    • A
      license
      B
      quality
      B
      maintenance
      Provides persistent memory for AI agents, including context storage, facts, plans, RAG search, code snippets, and conversation compaction, enabling state to survive across sessions and processes.
      14
      11 npm
      2
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Provides persistent, shared memory for AI agents by capturing conversations verbatim, distilling facts and summaries, and enabling retrieval through search, timeline, details, and explicit remember tools.
      MIT
    • F
      license
      Not graded
      quality
      D
      maintenance
      Provides AI agents with persistent, searchable memory that survives across conversations using semantic search, temporal versioning, and smart organization. Enables long-term context retention and cross-session continuity for AI assistants.
      14
      -
    • A
      license
      A
      quality
      D
      maintenance
      Provides persistent, self-optimizing memory for AI agents, enabling them to remember preferences and context across sessions and share knowledge across multiple agents.
      4
      10 npm
      ISC
    • A
      license
      Not graded
      quality
      C
      maintenance
      Gives AI agents persistent memory, handoffs, and shared context across sessions, enabling seamless continuity and multi-agent collaboration.
      14 npm
      69
      -

    TDQS

    A3.5/5.0

    Scored across 10 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: load/save manage persistence, add_message feeds buffer, get_context renders full context, get_lane pulls from a lane, apply_summary writes summaries, get_recent fetches recent messages for persona, apply_persona updates persona, status reports health, and set_normative sets policy. No two tools appear to overlap in function.

    Naming Consistency5/5

    All tools follow the prefix memory_ followed by a descriptive verb (load, save, add_message, get_context, get_lane, apply_summary, get_recent, apply_persona, status, set_normative). The pattern is consistent, with the only minor deviation being 'status' (a noun) but this is a common exception and does not break the overall predictability.

    Tool Count5/5

    10 tools is well within the ideal range for a memory management server. Each tool addresses a specific lifecycle or action (persistence, message ingestion, context retrieval, summarization, persona, status, policy) without redundancy, making the set appropriately scoped.

    Completeness4/5

    The tool surface covers the core memory lifecycle: load/save, add messages, get context, manage lanes and summaries, handle personas, and set normative policy. Minor gaps exist, such as no explicit clear/delete operations or direct retrieval of a single message, but these are easily worked around and do not break typical workflows.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues