Agent Cowork Memory

Name: Agent Cowork Memory
Author: rxthlessbeats

作者：rxthlessbeats版本 0.3.2i★ –i在你的电脑上运行

注册名称io.github.rxthlessbeats/agent-cowork-memory

安装

概览

作者提供的说明（英文原文）

Shared memory and delegation for Codex, Cursor, Claude Code, and OpenCode.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i1 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i尚未统计★ –

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：1 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
注册中心没有列出需要填写的密钥。

你需要

npm已安装 Node.js（用于 npx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "agent-cowork-memory": {
      "command": "npx",
      "args": [
        "-y",
        "agent-cowork-memory",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add agent-cowork-memory -- npx -y agent-cowork-memory mcp

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "agent-cowork-memory": {
      "command": "npx",
      "args": [
        "-y",
        "agent-cowork-memory",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "agent-cowork-memory": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "agent-cowork-memory",
        "mcp"
      ]
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 rxthlessbeats 验证，该账户拥有此仓库
… 尚未检查
仍在维护
我们还没有从 GitHub 读取这个仓库
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

星标数多于此分类中其他 5651 个服务器的 0%
发布到注册中心的时间比此分类中其他 5651 个服务器的 80% 更新
基础检查结果等于或优于此分类中其他 5651 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

Agent Cowork Memory 安全吗？

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

注册中心没有列出必需的密钥，不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于–，最新版本（0.3.2）于9天前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它？

同一分类中有：Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

作者：upstash

Up-to-date docs for AI agents

电脑或云端★ 64,224MIT昨天更新

安装

Codebase Memory

作者：DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

在你的电脑上运行★ 48,148MIT21天前更新

安装

Exa

作者：exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

在云端运行★ 5,213MIT上个月更新

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

Agent Cowork Memory (ACM)

 █████╗  ██████╗███╗   ███╗

██╔══██╗██╔════╝████╗ ████║ ███████║██║ ██╔████╔██║ ██╔══██║██║ ██║╚██╔╝██║ ██║ ██║╚██████╗██║ ╚═╝ ██║ ╚═╝ ╚═╝ ╚═════╝╚═╝ ╚═╝

Hit your Codex limit mid-task? Open Cursor, say "continue from Codex", and keep going. ACM gives Codex, Claude Code, Cursor, and OpenCode one shared memory, so you never paste context again, and any agent can put the others to work.

Verified by [benchmark](#benchmark): with Codex on 38 held-out tasks, ACM finished 223 of 228 runs, against 130 with a pasted summary. Cursor and OpenCode performed similarly with ACM and summaries.

Codex · Claude Code · Cursor · OpenCode

Demo

More demos on the ACM official site

Install

With Node 24 or newer:

npx agent-cowork-memory setup

Setup adds ACM to Cursor, and to Codex, Claude Code, and OpenCode when they are installed; Installed one later? Run setup again. Restart your agents, and ACM is available in every project.

Tested for real on Linux and WSL. macOS and Windows pass CI; real runs welcome.

Use

Memory Sharing

Open the same project in Codex and Cursor. To pick up a chat in the other agent, ask:

Use ACM to continue from Cursor.

Or, in Cursor:

Use ACM to continue from Codex.

Every agent can see every chat in the project. If there is more than one, the agent lists them (agent, time, thread, first message, and whether ACM started it for a delegated job) and asks you which one to continue. You can also name it:

Use ACM to continue the Codex chat about the trip.

Related work goes together in a thread: continuing a chat, or delegating from it, keeps the work on one thread, and a new chat can join one of the project's open threads. ACM keeps each thread's timeline as things happen (chats joining, jobs starting and finishing, notes added), so any agent can see where the work stands.

Ask your agent to remember a decision, and every agent in the project sees it. Notes stay true.

Delegate to other agents

Any agent can hand work to the others:

Tell codex to write plan.md, and claude to write packing.md.

Each agent gets a brief, joins the thread it was sent from, claims the files it edits so they don't collide, and reports back. Agents run in the background. With herdr installed, each one gets its own pane you can watch (herdr session attach acm). If you resumed a chat that's open in a herdr pane, work for that agent goes back to that chat, in its pane.

Benchmark

What it evaluates

How much of earlier chats' context survives when a new chat continues the work.
Each task is a small Python repo in two steps: earlier chats do step 1 and leave step 2's details in the chat.
The details sit in one short or long chat, spread over two chats, changed later, corrected mid-chat, or against a README that still says the old thing.
A run counts only if every hidden check passes, existing tests still pass, and no old or replaced value is implemented.

What we tested

Codex (gpt-6-luna, medium effort), Cursor (Grok 4.7 High), and OpenCode (GLM-5.3-Flash), continuing the work five ways:
no ACM;
ACM (*"Use ACM to continue from my last chat…"*);
the summary the earlier chat writes when asked;
a careful handoff note, including any Markdown files its turn wrote;
every earlier chat pasted in.
Held-out tasks written before the runs, with the analysis fixed in advance. Pilot checks and earlier-chat guards determine which tasks count for each agent.
Two independent histories, 3 runs per way per history; no ACM runs once per history.

Agent	Tasks	ACM	Summary pasted	Handoff note pasted in full	Full history pasted
Codex	38	223/228	130/228	214/228	222/228
Cursor	47	282/282	281/282	274/282	281/282
OpenCode	42	242/252	237/252	235/252	244/252

npm run bench        # offline checks, free

npm run bench:live # the live benchmark; spends your agent quota

MCP tools

Tool	What it does
`context`	Your thread and its timeline, the project's notes (after the first call, only what's new), open threads, recent jobs, who is working, and held files. Pass `hold` to claim files before writing, `thread` to join one, `done` to close yours. `stale` lists notes whose files changed, to re-check.
`note_add`	Saves a note every agent sees, and shows notes it may contradict. `tier`: `short` (default, kept 7 days) or `long`; `supersedes`: the note it replaces.
`note_search`	Finds notes and delegated jobs' results.
`chats`	Lists recent chats from every agent in the project, and marks the ones ACM started.
`resume`	Asks you which chat to continue when there are several, then reads it, with what you said in its thread's other chats, and joins its thread.
`delegate`	Starts other agents with a brief, in herdr panes or in the background, and waits for them.
`delegate_wait`	Keeps waiting on this chat's delegated agents.

ACM tells which chat it is in on its own; no tool needs a session or, from the project folder, a path (every tool takes an optional repo_path).

CLI

Command	What it does
`acm setup`	Adds ACM to your agents.
`acm mcp --harness`	Runs the MCP server; agents start it themselves.
`acm status [--repo ] [--chat ] [--harness ]`	The project's jobs, held files, and a chat's thread, as JSON.
`acm doctor`	Checks the install: Node, the database, herdr, and which agents are on PATH.
`acm backup [--to ]`	Copies the database.

--home (or ACM_HOME) moves ACM's state folder from ~/.agent-cowork-memory. Run them with npx -y agent-cowork-memory , or acm once it's installed globally.