原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
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LocalKeep

作者:zuneracodes版本 0.1.3i★ –i在你的电脑上运行
注册名称io.github.zuneracodes/localkeep

安装

概览

作者提供的说明(英文原文)

Local chronological memory banks you control; Claude recalls them via MCP.

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。

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)。
  • 需要你自己填写: LOCALKEEP_DATA_DIR, LOCALKEEP_DB_PATH

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

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": {
    "localkeep": {
      "command": "uvx",
      "args": [
        "localkeep"
      ],
      "env": {
        "LOCALKEEP_DATA_DIR": "your-value",
        "LOCALKEEP_DB_PATH": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add localkeep --env LOCALKEEP_DATA_DIR=your-value --env LOCALKEEP_DB_PATH=your-value -- uvx localkeep

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": {
    "localkeep": {
      "command": "uvx",
      "args": [
        "localkeep"
      ],
      "env": {
        "LOCALKEEP_DATA_DIR": "your-value",
        "LOCALKEEP_DB_PATH": "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": {
    "localkeep": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "localkeep"
      ],
      "env": {
        "LOCALKEEP_DATA_DIR": "your-value",
        "LOCALKEEP_DB_PATH": "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

  • LOCALKEEP_DATA_DIR env
    Optional directory for the SQLite DB (default: ~/.localkeep)
  • LOCALKEEP_DB_PATH env
    Optional full path to localkeep.db

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6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 zuneracodes 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 7248 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7248 个服务器的 30% 更新
  • 基础检查结果等于或优于此分类中其他 7248 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

LocalKeep 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(0.1.3)于3个月前进入注册中心。

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: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今天更新
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★ 48,148MIT20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。

LocalKeep

LocalKeep is for anyone who wants a chronological memory layer for chatbots where *they* directly control *what* the model remembers about them. Instead of forcing you to rely on a black-box cloud memory that the model invents around you that you can't even edit, LocalKeep lets you curate titled, dated, editable memory banks directly on your own machine where you write the entries and manage them locally via a localhost Hub UI. When a conversation requires your prior context, Claude queries your local data through a secure, native Model Context Protocol (MCP) connector.

Why use LocalKeep

AI Chat apps are great at *sounding* like they remember you, but struggle at recalling the exact thing you care about — *what* happened, on *which* date, about *whom*? Consumer memory features tend to lack the capacity for true temporal reasoning, flattening your history into a soft, generic vibe summary instead of understanding that Event A triggered Event B three months ago, causing its reasoning to fail when you need something specific: a life event, a research arc, a decision you logged months ago. Worse yet, consumer AI memory is a black box: you don't get to decide what the model chooses to remember about you, how it interprets your life, or when it invents context around you.

LocalKeep fixes both structural flaws at once by replacing fragile, model-invented timelines with a rigid, chronological source of your truth, all while giving *you* absolute editorial control. You decide exactly *what* the AI is allowed to know about you. You write the entries, you anchor the dates, and you keep them local on your own machine. Claude simply acts as the lookup engine via MCP when a conversation requires your prior context. LocalKeep bridges the gap between structured personal logging and intelligent AI retrieval, ensuring your context is curated by you—not hallucinated by an LLM.

Who it’s for

  • Anyone frustrated that chat memory can’t reliably fetch dated facts or understand timelines
  • People who already maintain meticulous personal diaries, work logs, or research archives. Instead of settling for a generic chat-app paraphrase, you get to inject your *exact* words and historical data into the prompt as an unyielding source of truth.
  • Users who trust Claude for its reasoning capability, but demand that their foundational context database remains stored locally under their own roof. (Note: Querying memories via MCP still sends the *retrieved text fragments* to Anthropic during the session).

What it is (and isn’t)

  • Is: A lightweight customizable local Hub UI to manage your dated memory banks, paired with an MCP server that Claude Desktop can call.
  • Isn’t: A standalone chat application, a cloud-hosted memory API, or a background utility that silently scrapes your personal conversations.

The Aesthetic Philosophy

The Hub UI intentionally adopts a retro, Windows 95/MS Paint-inspired homage with customizable features to ensure LocalKeep feels like a deeply personal tool rather than an impersonal, rigid dashboard. By putting adjustable interface elements right at your fingertips, the UI signals that you are entering an intimate, offline workshop for your mind—a space you can shape and reconfigure to feel entirely like your own.

Install

pip install localkeep

or: uv tool install localkeep

Then:

localkeep-hub          # http://127.0.0.1:8000

In Claude Desktop, register the MCP server (claude_desktop_config.json):

{

"mcpServers": { "localkeep": { "command": "localkeep-mcp", "args": [] } } }

If the GUI can’t find localkeep-mcp on your PATH, use the absolute path from which localkeep-mcp (the Hub’s Connect panel copies this for you).

Memories default to ~/.localkeep/localkeep.db when installed via pip. Override with LOCALKEEP_DATA_DIR or LOCALKEEP_DB_PATH.

Auto-use LocalKeep (important)

Claude will not reliably call MCP tools unless you also set Personal preferences:

  1. Claude Desktop → Settings → Profile → Personal preferences
  2. Paste the LocalKeep instructions (Hub → Connect → Copy instructions, or see src/localkeep/assets/claude-personal-preferences.txt)
  3. Quit Claude completely and reopen
  4. When LocalKeep asks to run a tool, click Always approve

Develop from source

git clone https://github.com/zuneracodes/localkeep

cd localkeep uv sync --group dev uv run localkeep-hub # http://127.0.0.1:8000

optional live reload:

LOCALKEEP_HUB_RELOAD=1 uv run localkeep-hub

From a source checkout, the DB lives in data/localkeep.db (gitignored).

Tests

These smoke-check the Hub, retrieval, and MCP tools so a fresh install still stores and recalls dated memories the way a real user would.

uv sync --group dev

uv run pytest

Tests start from an empty DB and create memories through Hub form POSTs (same path as a new user).

Privacy

Storage is local. Banks and memories live in your chosen DB path (~/.localkeep/ for pip installs, or data/localkeep.db in a checkout). There is no LocalKeep cloud and nothing is auto-scraped from chat. Theme colors stay in browser localStorage. Refreshing the Hub page or restarting localkeep-hub does not delete your banks — only removing the database file does.

Recall goes through Claude. The Hub and database stay on your machine, but when Claude calls a LocalKeep MCP tool, the matching memories are returned into that chat and Anthropic processes them like any other tool result. LocalKeep isn’t shipping your whole DB upstream — only what that lookup returns for the question at hand.

Contributing

Bug reports and pull requests are welcome via GitHub Issues. Please run uv run pytest before opening a PR.

License

MIT — see LICENSE.

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