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MemTensor

MemOS

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Alternatives to MemOS

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    Related Servers

    • memU MCP Server

      MonsterOne1
      A
      license
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      quality
      D
      maintenance
      Enables AI applications to use advanced memory management capabilities through the memU AI framework. Supports storing conversation memories, semantic retrieval, multi-user management, and memory statistics via standardized MCP protocol.
      3
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    • epitome

      gunning4it
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      quality
      D
      maintenance
      Provides a shared, persistent memory layer for AI agents, enabling them to recall, memorize, and review user information across different applications.
      8
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    • mind-mem

      ovidiu-eremia
      A
      license
      Not graded
      quality
      D
      maintenance
      Drop-in memory layer for AI coding agents, upgrading them from chat history to a governed Memory OS with hybrid search, contradiction detection, and safe governance.
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    Deploy Server
    One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

    TDQS

    A4.3/5.0

    Scored across 4 tools

    Disambiguation4/5

    The tools have distinct primary purposes: add_message for new memories, add_feedback for modifications/deletions without IDs, delete_memory for deletions with IDs, and search_memory for retrieval. However, add_feedback and delete_memory both handle deletion (one without IDs, one with), which could cause minor confusion about which to use when the user intent is deletion but IDs are ambiguous. The descriptions help clarify this boundary.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with snake_case: add_feedback, add_message, delete_memory, search_memory. The verbs (add, delete, search) are clear and aligned with their actions, and the nouns (feedback, message, memory) relate coherently to the domain of memory management.

    Tool Count5/5

    With 4 tools, this server is well-scoped for its purpose of memory operations. It covers the essential CRUD-like functions: create (add_message), read (search_memory), update/delete without IDs (add_feedback), and delete with IDs (delete_memory). The count is lean and each tool has a clear, non-redundant role in the workflow.

    Completeness4/5

    The tool set provides strong coverage for memory lifecycle operations: adding new memories, searching, and deletion (with and without IDs). The update functionality is handled indirectly via add_feedback for modifications, which is reasonable. A minor gap is the lack of a direct 'update_memory' tool for explicit modifications with IDs, but add_feedback covers this in a natural language way, and agents can work around this limitation.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

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