S
stoneskin/open-memex
Local-first memory layer for AI coding agents — Markdown as source of truth, MCP server + CLI, human-reviewed capture, team knowledge via git PRs.
无 SECURITY.md
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
安装与配置
- 复制上面的命令
- 粘成
claude_desktop_config.json里mcpServers的一项（本地服务器用 command + args，示例见 客户端接法） - 重启客户端
客户端配置（取自该仓库的安装命令）
{
"mcpServers": {
"stoneskin-open-memex": {
"command": "npx",
"args": ["-y", "open-memex"]
}
}
}解析自我们于 2026-10-26 抓取的该仓库 README；我们未执行过。
command/args 来自仓库写明的安装命令；不确定时请以该项目 README 为准。
VS Code（.vscode/mcp.json —— 键名是 servers）
{
"servers": {
"stoneskin-open-memex": {
"command": "npx",
"args": ["-y", "open-memex"]
}
}
}VS Code 顶层键是 <code>servers</code>，其余与上面那份相同。
Claude Code（命令行）
claude mcp add --transport stdio stoneskin-open-memex -- npx -y open-memex
Claude Code 不收 JSON 文件，用这条命令直接加。
配置项的键名以你的客户端为准：客户端与 CLI
- ★ 数取值
- 6 ★ · stoneskin/open-memex · 取自 GitHub 搜索 API · （2026-11-13 20:00:50 核对）
- 来源明细
- 收录自 punkpeye/awesome-mcp-servers 榜单（我们从中收集的条目之一） · 条目类型：MCP 服务
- 收录与活跃
- 收录于 2026-10-23 · 最近见到 2026-11-14 · 共见到 26 次 · 被 23 个来源列出
- 评分构成
- 综合分 2,300 · 6 ★ · 23 个来源 · mcp
- 安装
npx -y open-memex
常见问题（答案都来自我们的记录）
怎么安装？
该仓库给出的安装命令是
npx -y open-memex。我们的记录里它是仓库自己提供的；不保证在你的客户端上直接可用。它适合谁 / 用来做什么？
我们把它归在这些标签下: MCP 服务。标签来自条目自身，不是我们强加的分类。
谁维护它、还在更新吗？
仓库
stoneskin/open-memex；我们收录于 2026-10-23；最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。# open-memex
以下摘录自该仓库的 README（片段） · 在 GitHub 读完整 README →
> Persistent memory for your AI coding agents — on your machine, in plain Markdown, shared by every tool you code with.
中文文档
Every AI coding session starts from zero: you re-explain the project, the agent
rediscovers the same gotchas, and yesterday's decisions vanish when the chat
ends. open-memex gives your agents a memory that survives the session. Say
"remember: we deploy on Fridays" once, and next week Copilot, Cursor, opencode,
or Claude Code already knows — because they all read and write the same local
memory on your machine.
Free and open source (Apache-2.0). No account, no cloud, no telemetry —
everything lives on your machine, in files you can open and edit.
Local-first: memories are plain Markdown files (the source of truth) with
a rebuildable SQLite keyword index. Nothing leaves your machine unless you
explicitly share it.
One memory, every agent: wire up several editors with one command; they
share the same memory instead of keeping separate silos.
Precise synonym search: ship finds deploy, 单点登录 finds SSO —
a curated multilingual map of equivalents is indexed with every memory at
write time, so no related wording misses the right answer. Deterministic
and auditable, no embedding model required.
New here? This README takes you from install to a working memory in about a
minute. The concept guide explains the mental model in
depth once you're up and running.
## Contents
Quick start
Core concepts
Which editors, which features
Installation
Setting up your editor
What init changes on your machine
Capture: how memories get saved
Tools the agent gets
Memory types
Team workflow: sharing memories through Git
Retrieval: how memories come back
Security & data
Limitations
Upgrading
Storage layout
Config
CLI reference
MCP server
Scopes, in detail
Troubleshooting
FAQ
Project status
## Quick start
You need Node.js ≥ 22.14 (check with node -v). Then:
sh
npm install -g open-memex
open-memex init
init detects the editors you have installed (VS Code, Cursor, opencode, and
Visual Studio when your project has a solution file) and connects each one to
open-memex. Restart your editor afterwards.
See it work (30 seconds):
sh
open-memex add "This project deploys on Fridays"
Now open a new chat in your editor and ask your agent: "When does this project
deploy?" It already knows — no re-explaining. That round trip, capture once and
recall forever, is the whole product. Everything below is detail.
Optional but recommended — check everything is wired up:
sh
open-memex doctor
## Core concepts
Four ideas explain almost everything open-memex does.
1. Two scopes: project and personal.
Every memory belongs to one of two places:
project — knowledge about one codebase (decisions, constraints, lessons).
Scoped to the current repo automatically; you never set this up by hand.
personal — knowledge about you (preferences, habits) that applies in
every project. It lives only on this machine and can never be shared into a
repo.
Facts about you ("I prefer concise diffs") go to personal; everything else
defaults to the current project.
2. Capture → recall.
Memories are saved as small Markdown files, one fact each. On the first turn of
every new session, open-memex hands your agent the most relevant ones
中文文档
Every AI coding session starts from zero: you re-explain the project, the agent
rediscovers the same gotchas, and yesterday's decisions vanish when the chat
ends. open-memex gives your agents a memory that survives the session. Say
"remember: we deploy on Fridays" once, and next week Copilot, Cursor, opencode,
or Claude Code already knows — because they all read and write the same local
memory on your machine.
Free and open source (Apache-2.0). No account, no cloud, no telemetry —
everything lives on your machine, in files you can open and edit.
Local-first: memories are plain Markdown files (the source of truth) with
a rebuildable SQLite keyword index. Nothing leaves your machine unless you
explicitly share it.
One memory, every agent: wire up several editors with one command; they
share the same memory instead of keeping separate silos.
Precise synonym search: ship finds deploy, 单点登录 finds SSO —
a curated multilingual map of equivalents is indexed with every memory at
write time, so no related wording misses the right answer. Deterministic
and auditable, no embedding model required.
New here? This README takes you from install to a working memory in about a
minute. The concept guide explains the mental model in
depth once you're up and running.
## Contents
Quick start
Core concepts
Which editors, which features
Installation
Setting up your editor
What init changes on your machine
Capture: how memories get saved
Tools the agent gets
Memory types
Team workflow: sharing memories through Git
Retrieval: how memories come back
Security & data
Limitations
Upgrading
Storage layout
Config
CLI reference
MCP server
Scopes, in detail
Troubleshooting
FAQ
Project status
## Quick start
You need Node.js ≥ 22.14 (check with node -v). Then:
sh
npm install -g open-memex
open-memex init
init detects the editors you have installed (VS Code, Cursor, opencode, and
Visual Studio when your project has a solution file) and connects each one to
open-memex. Restart your editor afterwards.
See it work (30 seconds):
sh
open-memex add "This project deploys on Fridays"
Now open a new chat in your editor and ask your agent: "When does this project
deploy?" It already knows — no re-explaining. That round trip, capture once and
recall forever, is the whole product. Everything below is detail.
Optional but recommended — check everything is wired up:
sh
open-memex doctor
## Core concepts
Four ideas explain almost everything open-memex does.
1. Two scopes: project and personal.
Every memory belongs to one of two places:
project — knowledge about one codebase (decisions, constraints, lessons).
Scoped to the current repo automatically; you never set this up by hand.
personal — knowledge about you (preferences, habits) that applies in
every project. It lives only on this machine and can never be shared into a
repo.
Facts about you ("I prefer concise diffs") go to personal; everything else
defaults to the current project.
2. Capture → recall.
Memories are saved as small Markdown files, one fact each. On the first turn of
every new session, open-memex hands your agent the most relevant ones
收录徽章（可选）
想把收录标记放进 README 就复制这行，可选，不影响收录。
[](https://anclum.com/zh/s/stoneskin-open-memex/)
- 来源
- awesome · https://github.com/stoneskin/open-memex
- 按领域浏览
- MCP 服务
- Traction
- 6 ★
- 收录来源
- 23 个独立来源
- 收录于
- 今天
- 安全策略
- 我们没在该仓库根目录找到
SECURITY.md（这不代表不安全）
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