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Alternatives to MeMCP

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    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      Gives AI agents a long-term memory layer over plain Markdown notes, letting them run ranked, citable searches, record new facts, and inspect conflicts and stale entries. Results carry freshness labels, supersession history, and audit fields like search timestamp and no-match status so agents can prove a search actually ran.
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI agents to capture, structure, remember, and retrieve source-backed memory as local Markdown files, with reviewable writes and no cloud dependency.
      218
      MIT
    • A
      license
      A
      quality
      A
      maintenance
      Enables multiple AI agents on one machine to write, search, fetch, link, and give feedback on a shared local store of Markdown-backed facts, preferences, and conventions that persists across sessions. Memories gain confidence as different hosts confirm their use and can be distilled into denser ones, so agents stop re-discovering the same context.
      5
      507 PyPI
      1
      MIT
    • A
      license
      Not graded
      quality
      A
      maintenance
      Local-first, file-based memory layer for AI agents — one shared Markdown vault across Claude, Codex, Gemini, Cursor and any MCP client. Provides read/write memory tools with an audit trail, per-agent trust levels, and Git sync; no cloud and no lock-in.
      2
      MIT
    • A
      license
      Not graded
      quality
      C
      maintenance
      Durable memory with sources, proof, history, and review for MCP-capable agents. It turns a Markdown/Obsidian vault into a local knowledge substrate, enabling agents to store, search, and retrieve governed knowledge.
      26,367 PyPI
      9
      AGPL 3.0
    • A
      license
      B
      quality
      B
      maintenance
      Enables AI agents to maintain a local, event-sourced long-term memory with semantic retrieval, decision confidence checks, and proactive recalls, ensuring data never leaves the machine.
      23
      3
      MIT

    Maintenance

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