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Alternatives to AI Memory MCP Server

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    Related Servers

    • A
      license
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      Enables AI coding agents to maintain a private, local-first persistent memory by automatically saving, searching, and retrieving structured project memories through MCP, with hybrid keyword and embedding search, feedback-driven ranking, and no cloud dependency.
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      MCP-native persistent memory layer for AI agents across Claude Code, Cursor, VS Code, and OpenClaw. Powered by hybrid vector search, BM25, and cross-encoder reranking with a published 73.1% LoCoMo benchmark accuracy.
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      Apache 2.0
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      license
      A
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      Local-first persistent memory for coding agents and MCP clients. It keeps important project context across sessions and reduces wasted tokens by retrieving only relevant memories instead of replaying unnecessary history.
      8
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    • A
      license
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      quality
      B
      maintenance
      Enables AI coding agents and assistants to share a local-first, token-efficient persistent memory layer across MCP-compatible runtimes, storing typed project facts, decisions, failures, and solutions with temporal validity. It supports offline use and Postgres-compatible storage, so agents can retrieve relevant context without re-embedding entire repositories.
      Apache 2.0
    • A
      license
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      quality
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      Enables AI coding agents to retrieve and manage code context with hybrid search, project memory, and observability via MCP tools.
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    • A
      license
      Not graded
      quality
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      Provides AI coding agents with a persistent memory layer to save, recall, update, and track memories across sessions and repositories using hybrid semantic search.
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    TDQS

    A4/5.0

    Scored across 8 tools

    Disambiguation5/5

    Each tool has a clearly distinct purpose: forget (delete), get_memory (by id), list_memories (filtered browsing), recall (semantic search), remember (create), search_memories (structured filter), update_memory (modify), who_am_i (identity). Despite some overlap between list and search, descriptions differentiate them well.

    Naming Consistency3/5

    Naming conventions are mixed: three tools are single verbs (forget, recall, remember), four are verb_noun (get_memory, list_memories, search_memories, update_memory), and one is a phrase (who_am_i). This inconsistency, while readable, lacks a uniform pattern.

    Tool Count5/5

    With 8 tools, the set is well-scoped for a memory server. Each tool serves a distinct CRUD or auxiliary role, covering creation, retrieval (multiple methods), update, deletion, and system info. No tool seems superfluous or missing.

    Completeness5/5

    The tool surface provides full lifecycle coverage: remember (create), get_memory/list/recall/search/who_am_i (read), update_memory (update), forget (delete). It also supports linking via recall. No obvious gaps for the intended personal memory domain.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues