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Alternatives to memory-tree

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    Related Servers

    • A
      license
      Not graded
      quality
      B
      maintenance
      An MCP server that lets multiple AI coding agents share state, preserve context across sessions, and coordinate via a knowledge graph, messaging, and branch-preserving checkpoint/resume with conflict handling.
      63 npm
      1
      Apache 2.0
    • A
      license
      Not graded
      quality
      C
      maintenance
      Local-first MCP server that persists AI coding agent memory and session context, enabling seamless resume across sessions with searchable memories and checkpoints.
      6 npm
      1
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      MCP server providing persistent, local-first memory for AI agents via Markdown files in a git repo, with search, branching, and auditability.
      11 npm
      2
      MIT
    • A
      license
      Not graded
      quality
      B
      maintenance
      A self-hosted MCP server that gives every connected AI app (ChatGPT, Claude, Gemini, Cursor, Codex, Copilot) one shared memory of ideas, decisions, todos, notes and standing instructions to read and write. It also lets apps start multi-step tasks and save checkpoints on a git branch, so when one hits its usage limit another can resume the work and the original app can later review what changed.
      5
      AGPL 3.0
    • A
      license
      Not graded
      quality
      D
      maintenance
      A local-first MCP server providing persistent, layered memory (episodic, semantic, procedural, resource) for AI agents, with search, versioning, and session management via a single SQLite file.
      78 npm
      3
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      A local-first MCP server for AI programming branch notes and mainline decision logging, supporting branch management, summary merging, and Markdown export with optional Git-mode for isolated branch conversations.
      3
      MIT