cogito-mem (Cogi)

Name: cogito-mem (Cogi)
Author: meridian21lab

作者：meridian21lab版本 0.3.0i★ –i在你的电脑上运行

注册名称io.github.meridian21lab/cogito-mem

安装

概览

作者提供的说明（英文原文）

Local long-term memory for Claude Code and other agents: every message kept word for word, no cloud.

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非常新↓ 161/周 · ★ –

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: 文档、表格与办公

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）。
需要你自己填写： COGITO_MEM_NAMESPACE

你需要

PyPI已安装 Python 的 uv（用于 uvx 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": {
    "cogito-mem": {
      "command": "uvx",
      "args": [
        "cogito-mem",
        "mcp"
      ],
      "env": {
        "COGITO_MEM_NAMESPACE": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add cogito-mem --env COGITO_MEM_NAMESPACE=your-value -- uvx cogito-mem mcp

运行前请先填写空着的值。

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": {
    "cogito-mem": {
      "command": "uvx",
      "args": [
        "cogito-mem",
        "mcp"
      ],
      "env": {
        "COGITO_MEM_NAMESPACE": "your-value"
      }
    }
  }
}

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": {
    "cogito-mem": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "cogito-mem",
        "mcp"
      ],
      "env": {
        "COGITO_MEM_NAMESPACE": "your-value"
      }
    }
  }
}

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。

需要你填写的值

COGITO_MEM_NAMESPACE env
The memory's name (default: -hollow).

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9日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 meridian21lab 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“文档、表格与办公”中的其他服务器比较i

星标数多于此分类中其他 3601 个服务器的 0%
发布到注册中心的时间比此分类中其他 3601 个服务器的 83% 更新
基础检查结果等于或优于此分类中其他 3601 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

cogito-mem (Cogi) 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（0.3.0）于5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 Python (uv)。

有什么可以替代它？

同一分类中有：Agent-Native Calendar, Excel MCP Server, MCP Server for Excel

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：↓ 每周下载量i★ 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

Agent-Native Calendar

Agent-Native Google Calendar - manage events, sync, and public booking

作者：BuilderIO广泛使用★ 76202个月前更新

在云端运行

安装

Excel MCP Server

Create and edit Excel files with AI: charts, PivotTables, formulas. No Excel needed.

作者：haris-musa广泛使用↓ 5万/周★ 42768天前更新

在你的电脑上运行

安装

MCP Server for Excel

Excel automation for AI - Sheets, Power Query, DAX, VBA, Tables, Ranges and more. Windows only.

作者：sbroenne正在增长↓ 4321/周★ 8475天前更新

在你的电脑上运行

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。

cogito-mem

Long-term memory for Claude Code, on your own machine. Cogi the squirrel keeps every message you and Claude exchange, and finds the right one again, even in over a million tokens of history. No API key, no cloud, no AI calls to store.

Why try it

Claude can look back. Every message and reply is kept word for word, with its date. When something has dropped out of the context window, or happened last month, Claude searches for it and gets your exact words back.
It remembers what you did, too. The commands you ran (and whether they failed), the files you touched, what each sub-agent reported, and the lines of output that say how a command went: errors, metrics, how a long run ended.
Private and free. One folder on your computer. No account, no API key, no AI calls to save a message. Nothing leaves your machine.
Tested. In LongMemEval's long test, each question hides its answer in about 480 past sessions, some 1.2 million tokens. The past session holding the answer is among the first five Cogi finds for 93.0% of 500 questions, with no AI model involved, ahead of four other local memory plugins we ran on the same questions (86.6–89.8% at their best settings). On the short test, with about 50 sessions, it is 99.0%, level with the best. On LoCoMo, with GPT-5 mini answering, the 1,000 tokens Cogi hands back answer 89.4% of questions right, against 94.1% from rereading the whole conversation: 95% of the quality while the model reads about 9 times fewer tokens. A search over 10 million tokens takes 26 ms on a laptop CPU. See the results.

Install

You need Claude Code and uv, on macOS or Linux (Windows is experimental). Then, in a terminal:

claude plugin install cogito-mem --marketplace meridian21lab/cogito-mem

The first start downloads the model (310 MB, about a minute). To get updates, turn on auto-update once: /plugin → *Marketplaces* → *cogito-mem* → *Enable auto-update*.

Step-by-step guide · Codex, Claude Desktop, Docker

Try it

Tell Claude: *Let's call the staging server "acorn".*
Clear its short-term memory: /clear
Ask: *What did we call the staging server?* Claude answers "acorn": Cogi brought it back.

What Cogi runs, downloads and stores

Runs: four Claude Code hooks and one MCP server, cogi. Each runs the released cogito-mem package from PyPI at the exact version the plugin pins (uvx cogito-mem== ); the plugin's uv.lock lists that release and numpy with their checksums. After each reply and at the end of a session, the hooks save the new messages from the session's transcript. At the start of a session and with each prompt, they add the most relevant memories (about 400 tokens per prompt, each line with an id Claude can open). The MCP server gives Claude three tools, memory_query, memory_open and memory_append, answered by a small service that listens on your computer only (127.0.0.1:7327).
Downloads, once, over HTTPS: cogito-mem and its one dependency, numpy, from PyPI (by uv); llama.cpp's llama-server from llama.cpp's official GitHub releases (skipped if you already have it); and the EmbeddingGemma 2 model (310 MB) from Hugging Face. After that, Cogi makes no network calls.
Stores: everything in ~/.cogito-mem/ on your computer: your messages, a short note of what each turn did, what each sub-agent reported back, and at most 800 characters of each command's output (errors, metrics, how a long run ended), in one SQLite file. Common forms of API keys, tokens, private keys and passwords are replaced with [redacted] before anything is saved; the rest of tool output and what Claude's Read tool returns are never saved. Redaction goes by patterns, so others can get through. Sessions from before the install are read only if you ask (cogito-mem capture claude-code --all), and old sessions may hold secrets the redaction misses. Text inside … is skipped, and COGITO_MEM_CAPTURE=off pauses saving.
Sends: nothing. No account, no analytics, no telemetry. (The optional benchmark command, cogito-mem eval locomo-qa, which only you would run, sends benchmark questions to the LLM API you set up for it, with your own key.)
Removes cleanly: claude plugin uninstall cogito-mem@cogito-mem, then delete ~/.cogito-mem.

Every file, download and connection, with links to the source: What you install.

How it compares

	cogito-mem	claude-mem	Mem0 plugin	cognee plugin	Supermemory plugin
AI calls to store a message	none	an observer model per tool call (Haiku on your Claude plan by default)	extraction on Mem0's servers	extraction with your LLM key or `claude -p`	in Supermemory's service
Account or API key	none	optional sign-in	Mem0 Platform API key	an LLM key or the Claude CLI	API key or login
Where your memory lives	your computer	your computer (cloud sync optional)	Mem0's cloud	your computer (cloud optional)	Supermemory's cloud (local mode available)
What comes back	your exact words, with dates	AI-written observations	extracted memories	graph facts and summaries	extracted memories
Searchable after	the same turn	the observer's run	a batch (every 5 exchanges)	the next graph run	the background save

Keep your project's rules in CLAUDE.md, and let Cogi remember what happened.

Learn more


How it works	Collect, keep, find: what Cogi stores and how it finds it
Results · Benchmarks	The numbers, and how to reproduce them
API & MCP · Reference	HTTP, Python, terminal, settings, FAQ, roadmap
What you install · Privacy · Terms	Every file, download and connection; privacy and terms
Development	Running the tests and the evaluations

Early access. v0.2 is new, built and tested (over 200 tests), and still being measured. Feedback and issues are very welcome.

License

MIT