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Related Servers

Alternatives to codemem

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    Related Servers

    • A
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      A persistent memory MCP server for Claude Code that enables long-term recall across sessions via hybrid search, code intelligence, and tools for reading/writing memory.
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    • A
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      MCP server that provides cross-session persistent memory for AI coding assistants using local vector database and semantic search, enabling automatic recall of project context, issues, and tasks.
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    • F
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      MCP server that provides persistent long-term memory for Claude Code, enabling storage, search, and retrieval of project knowledge across sessions.
      -
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      MCP server that gives OpenCode a persistent, graph-based memory with semantic search, iterative retrieval, and session-aware knowledge management. It supports capturing fleeting and permanent notes, distilling insights, tracking mistakes and fixes, and auto-archiving stale memories.
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    • A
      license
      Not graded
      quality
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      maintenance
      Persistent memory MCP server for Claude Code that captures and recalls project context across sessions, eliminating the need to re-explain architecture and decisions daily.
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    • A
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      MCP server that captures and recalls coding session memory (failures, decisions, diffs) for AI agents, enabling cross-agent continuity and preventing repeated mistakes.
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    TDQS

    B3.3/5.0

    Scored across 14 tools

    Disambiguation4/5

    Most tools are clearly distinct: memory_search vs memory_search_index differ by return format, memory_get vs memory_get_observations differ by cardinality, and memory_pack is explicitly for context building. A couple of retrieval tools could be confused, particularly memory_timeline and memory_expand, which both involve surrounding context.

    Naming Consistency4/5

    All tools share the memory_ prefix and use lowercase snake_case, making the set feel predictable. Minor inconsistency exists in mixing verb forms (memory_search, memory_expand, memory_get) with noun or adjective forms (memory_schema, memory_recent, memory_timeline), but the overall pattern is still coherent.

    Tool Count4/5

    14 tools is on the higher end of the well-scoped range, and most tools serve a distinct retrieval or lifecycle purpose. The count is slightly heavy due to many specialized read/search variants, but it remains reasonable for a memory-management server.

    Completeness3/5

    The core memory lifecycle is mostly covered: create via memory_remember, read via memory_get/get_observations/search/recent, and soft-delete via memory_forget. However, there is no memory_update or memory_edit tool, which is a notable gap for managing evolving memories.

    Maintenance

    ActivityActive
    ResponsivenessSlow