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aivectormemory

by GolderBrother
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    • io.github.cdnsteve/sugar

      Alexander11890
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      Gives AI coding agents persistent, local-first memory so they can store and recall decisions, preferences, error patterns, and cross-project guidelines, retrieving relevant context by semantic search without external API calls. It also optionally exposes an autonomous task queue that reads the same memory to execute and track queued work.
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    • Sugar

      rSenturk54927
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      Provides a local-first persistent memory layer that lets AI coding agents store, recall, and semantically search project-specific and cross-project knowledge across sessions, so context, decisions, and guidelines survive between conversations. Runs entirely on the user's machine with SQLite and no API keys, and optionally supports autonomous task-queue execution built on the same memory.
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    • io.github.cdnsteve/sugar

      Sebastien94506
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      quality
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      Gives AI coding agents persistent, local-first memory so they can store, semantically search, and recall decisions, preferences, error patterns, and cross-project guidelines directly during a session. It also optionally queues tasks for autonomous execution against that same memory.
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    • io.github.cdnsteve/sugar

      Wulff641
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      Provides AI coding agents with a local-first, persistent memory layer so they can store and semantically recall project-specific and cross-project knowledge, conventions, and error patterns during sessions. It also optionally enables autonomous task queue execution and issue resolution driven by that same memory.
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    • Sugar

      Benjaminn581
      F
      license
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      quality
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      Enables AI coding agents to read and write persistent, local-first memory across sessions and projects, with semantic search, global guidelines, and optional autonomous task execution.
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    Deploy Server
    Context All Your Agents Can ShareAgents share what they learn, hand off work, and hold it when you switch models. Start with 5 GB free.fulcradynamics.comAd

    TDQS

    B3.4/5.0

    Scored across 8 tools

    Disambiguation4/5

    remember/recall/forget form a clean memory CRUD triad, and track/task/readme are distinct. However, auto_save ("save user preferences") overlaps conceptually with remember, which already supports user-level storage, creating a potential confusion point.

    Naming Consistency3/5

    Memory tools use verbs (remember, recall, forget) while track, task, status, and readme are bare nouns, and auto_save uses verb_noun. The convention is mixed but each name is still readable and guessable.

    Tool Count4/5

    Eight tools is a well-scoped set for a memory/session/task server, especially since track and task bundle multiple sub-actions internally. Slightly on the lean side but each tool earns its place.

    Completeness4/5

    Covers memory lifecycle (remember/recall/forget), session state, issue tracking, task management, and readme generation. Minor gaps like listing/exporting all memories or explicit memory update exist, but remember's auto-dedupe mitigates this.

    Maintenance

    ActivityInactive
    ResponsivenessNo issues

    Resources