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dsh-vector-memory

已验证 · 实测可装 Bryan-cmf

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—语言
2026-08-17最近推送
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功能简介

DSH-Plugin: durable agent memory core - mem_save/mem_search/mem_health backed by storageDomain (survives restarts), 記憶 view tab.

✅
我们的评价
可用 — 实测通过,早期项目

DSH-Plugin: durable agent memory core - mem_save/mem_search/mem_health backed by storageDomain (survives restarts), 記憶 view tab. 实测能干净安装、正常启动。早期项目,但功能可用。

「已验证」表示我们的自动化 CI 在干净 profile 里实际执行了 dsh plugin add 并启动成功——仅此而已。功能描述与版本兼容性均为作者声明。这不是安全审计,也不代表对第三方代码的背书。

README

⚠️ 此套件已併入 @bryan-cmf/dsh-insights(2026-08-17)。此 repo 僅保留作合併前歷史,後續迭代請到 dsh-insights。

🧠 Vector Memory — DSH-Plugin

可持久化的 Agent 記憶核心——mem_save / mem_search / mem_health,跨 session、跨重啟,零外部依賴。

npm
License: MIT
DSH

A DeepSeek Harness plugin
that gives your agents durable, cross-session memory — the same
mem_save / mem_search contract as the original
Bryan-cmf/vector-memory MCP
server, but natively on DSH.

Why a native rewrite (and what changed)

The 2026 memory landscape made self-hosting a Qdrant + BGE-m3 stack a
commodity (Zep / Mem0 / Letta / LangMem all offer managed embeddings + graph
memory). This package keeps the agent-facing contract and drops the
infrastructure:

Aspect Old (MCP server) This plugin
Storage Qdrant (Docker) + BGE-m3 (~2GB) DSH storageDomain — durable JSON backend, zero setup
Retrieval Vector similarity v1: deterministic keyword scoring + recency; embeddings pluggable in v2
Interface MCP stdio (Claude/Cursor/…) Native tools (mem_save / mem_search / mem_health) + vectorMemory service
Persistence Manual install script Bundle row — it just works

Tools

Tool Effect
mem_save { content, tags?, ttlDays? } → durable memory, returns id
mem_search { query, limit? } → ranked hits (score, content, tags, created)
mem_health record count, expired count, domain status, TTL policy

Other plugins can inject: ['vectorMemory'] and call save / search /
health directly.

Dashboard

The client half registers a 「記憶」view tab (order 30, right of
chat / 軌跡 / 觀測) listing this session's saved/searched items live.

Install

"dsh": { "profile": { "bundles": ["@bryan-cmf/dsh-vector-memory"] } }

⚠️ This row publishes the vectorMemory service — it must live in the
host composition (process-global). If you mount it from an agent preset
instead, wrap it in a group with an isolate realm (see the DSH
composition docs).

Requirements

  • DSH >= 0.1.0-rc.6 — services: tools, storageDomain (domain layer +
    a storage backend, e.g. dsh-storage-json, are part of the shipped
    dsh-base bundle)

Configuration

Key Default Meaning
ttlDays 90 Default memory TTL; 0 = forever
maxResults 10 Default mem_search result count

Roadmap

  • v2: pluggable embedding backends (hosted embedders or Qdrant REST)
  • v2: MCP stdio dual-exit so the same store serves Claude Desktop / Cursor
  • v2: memory curation (merge/dedupe/forget jobs)

Development

pnpm install --store-dir .pnpm-store
pnpm build

License

MIT

安装

🧩 让 Agent 自动装(推荐)

装一次目录插件,之后本站所有插件都能让 DeepSeek Harness 自动找、自动装:

dsh plugin add dshbase-catalog

然后对 agent 说「帮我装 dsh-vector-memory」,它会在目录里找到并自动安装。文档:dshbase-catalog · 已验证场景包。

该插件是 GitHub 源码(未发 npm)——直接从仓库装:

Web profile:

dsh plugin --profile web add github:Bryan-cmf/dsh-vector-memory

Headless(CLI)profile:

dsh plugin --profile headless add github:Bryan-cmf/dsh-vector-memory

实测报告

验证通过:从 GitHub 源码完成 L1 安装 + L2 加载 + L3 运行(dsh 0.1.0-rc.6)。

安全:尚未扫描——我们的每日静态扫描将很快覆盖它。

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