
Agent Cowork Memory
io.github.rxthlessbeats由 GitHub 账号 rxthlessbeats 发布v0.3.2更新于 Oct 29, 2026
Shared memory and delegation for Codex, Cursor, Claude Code, and OpenCode.
发布方自己的服务:Memory.fit
概览
为 Codex、Claude Code、Cursor 和 OpenCode 提供共享的项目记忆,让助手能接续其他代理的对话、共享笔记并分派任务。
- 可以做什么
- 读取线程上下文、时间线、项目笔记、开放线程、近期任务和已占用文件
- 保存所有代理可见的笔记,搜索笔记与委派任务结果,标记过期笔记
- 列出各代理的近期对话,并接续选定的对话加入其线程
- 把任务连同简要说明分派给其他代理并等待结果
- 通过命令行执行 setup、status、doctor 和 backup 等命令
- 适用场景
- 适合在同一项目上交替使用多个编程代理、希望上下文自动延续而不必粘贴摘要的场景,也适合让一个代理在后台把任务交给另一个代理。
- 运行要求
- 以 npx 运行的本地进程,需要 Node 24 或更高版本。setup 会把 ACM 加入 Cursor,以及已安装的 Codex、Claude Code 和 OpenCode,之后需重启这些代理。状态保存在主目录下的文件夹中,可用 ACM_HOME 更改位置。可选安装 herdr 以显示独立窗格。
安装
在 SourceWeft 中
- 打开 控制台中的 Agent Cowork Memory,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
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: 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.
[GitHub Release]
[npm]
[CI]
[License]
[M8ven Score]
[Agents supported]
[Node]
[Benchmark]
[MCP supported]
[CLI supported]
[Codex icon] Codex · [Claude Code icon] Claude Code · [Cursor icon] Cursor · [OpenCode icon] OpenCode
Demo
[Claude Code delegates to Codex, Cursor, and OpenCode through ACM]
More demos on the ACM official site
Install
With Node 24 or newer:
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.
MCP tools
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
--home <dir> (or ACM_HOME) moves ACM's state folder from ~/.agent-cowork-memory. Run them with npx -y agent-cowork-memory <command>, or acm once it's installed globally.
来源:README.md,提交 be804bc
工具
0版本历史
4- v0.3.2最新Oct 29, 2026
- v0.3.1Oct 20, 2026
- v0.3.0Oct 6, 2026
- v0.2.1Sep 30, 2026
评分
已满足适用检查项的 50%
该评分衡量此收录条目的完整程度,依据注册中心条目、端点与公开来源计算得出。它不是对服务器本身的评价,也不表示服务器安全或当前可用:可连通性是带日期的检查结果,评分也不包含安装量或用户评价。
- 近 30 天内可连通25 分
请保持端点能够响应 MCP 握手;SourceWeft 每 30 天探测一次。
- 已声明认证方式10 分
请在注册中心条目中声明凭据请求头,或保持端点能够响应探测,以便判定其认证方式。
- 已列出工具15 分
请让服务器在无凭据时响应 tools/list,或发布可在沙箱中无凭据启动的软件包。
- 描述必需15 分
- 图标10 分
- 文档15 分
- 许可证10 分
其他 Memory 集成

Memory.fit
fit.memory官方发布者
托管式 Memory.fit 服务器,让 AI 读取你的训练、睡眠、恢复与饮食数据,并写回每周计划、每日目标和饮食计划。
pg.ddx.io: the PostgreSQL community's memory
io.ddx.pg官方发布者
pg.ddx.io: the PostgreSQL community's memory 的托管 MCP 服务,由 pg.ddx.io 发布;无需登录;Streamable HTTP;29 个工具。
var.gg Naming Memory
gg.var官方发布者
远程 MCP 服务器,可根据领域概念推荐并检索韩、日、中、越、英多语言的代码标识符名称,并提供 ERD 结构查询。

Memoria — Deterministic AI Memory & Code Intelligence MCP
由 GitHub 账号 kolivritech 发布
远程 MCP 服务器,为 AI 编程助手提供确定性的长期记忆和代码智能工具,召回过程不消耗 LLM token。

thron-memory
由 GitHub 账号 jacobbarglof 发布
为所有支持 MCP 的 AI 应用提供一份共享的私有记忆,以纯文本笔记页形式供助手搜索、读取和更新。