deepseekplugins

DeepSeek Harness plugin

dsh-vector-memory

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

Workflow & Automation
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Source facts

Repository
Bryan-cmf/dsh-vector-memory
Latest update
Aug 17, 2026
Category
Workflow & Automation
GitHub stars
0
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

Install

Start with a prompt that asks an agent to review the GitHub repository and source. Switch to the command if you want to install it yourself.

Copy this prompt into DSH, Codex, or another agent and ask it to review the GitHub repository and source first.

Do not install or run any commands yet. Read this plugin's GitHub repository, README, and relevant source code. Then answer the questions below clearly and directly so I can decide whether it fits my needs:

1. What is this plugin, and what problem does it solve?
2. Who is it for, and what are its typical use cases?
3. How is it used after installation? Include one minimal example.
4. What known limitations or privacy, security, compatibility, or maintenance risks does it have?
5. Give a clear recommendation: recommend, conditionally recommend, or do not recommend, with reasons.

Distinguish statements documented by the repository, inferences from source code, and unknowns. If evidence is insufficient, say so explicitly. Do not guess or simply repeat the README.

GitHub: https://github.com/Bryan-cmf/dsh-vector-memory
Plugin: dsh-vector-memory
Author: Bryan-cmf

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer3 files
README.mdSource · read only

> ⚠️ 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](https://www.npmjs.com/package/@bryan-cmf/dsh-vector-memory) ![License: MIT](LICENSE) ![DSH](https://github.com/deepseek-ai/deepseek-harness)

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:

AspectOld (MCP server)This plugin
StorageQdrant (Docker) + BGE-m3 (~2GB)DSH storageDomain — durable JSON backend, zero setup
RetrievalVector similarityv1: deterministic keyword scoring + recency; embeddings pluggable in v2
InterfaceMCP stdio (Claude/Cursor/…)Native tools (mem_save / mem_search / mem_health) + vectorMemory service
PersistenceManual install scriptBundle row — it just works

Tools

ToolEffect
mem_save{ content, tags?, ttlDays? } → durable memory, returns id
mem_search{ query, limit? } → ranked hits (score, content, tags, created)
mem_healthrecord 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

KeyDefaultMeaning
ttlDays90Default memory TTL; 0 = forever
maxResults10Default 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

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