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PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

KEPTA — the memory for AI systems

作者:DamianTodorovic版本 3.4.0i★ –i在你的电脑上运行
注册名称io.github.DamianTodorovic/kepta

安装

概览

作者提供的说明(英文原文)

Local encrypted memory for AI: hybrid search, 8 MCP tools, one file you own. Free, 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。

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?

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": {
    "kepta": {
      "command": "npx",
      "args": [
        "-y",
        "kepta-mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add kepta -- npx -y kepta-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": {
    "kepta": {
      "command": "npx",
      "args": [
        "-y",
        "kepta-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": {
    "kepta": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "kepta-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 DamianTodorovic 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 7257 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7257 个服务器的 60% 更新
  • 基础检查结果等于或优于此分类中其他 7257 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

KEPTA — the memory for AI systems 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(3.4.0)于24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。

KEPTA — the memory for AI systems

Your AI forgets everything. Every chat starts from zero.

KEPTA is the fix: one local, encrypted memory that every AI reads and writes — Claude, Cursor, Gemini CLI, Cline, any MCP client, and scripts over HTTP. No cloud. No account. One file you own.

Everything an AI system learns goes into an encrypted knowledge base on your own computer — and every AI recalls it in milliseconds, however long the context grows. Documents, decisions, client knowledge, whole chat histories: remembered, linked, contradicted, superseded — never lost.

This repository is the source-available core (BUSL-1.1 — every line public, converts to AGPL-3.0-or-later four years after each release): the memory engine, the MCP server, the HTTP API — and the Python client, which is MIT so any Python project can embed it. Everything that makes the memory smart lives in this free engine. There are no tiers inside the memory — nothing is held back to sell anything.

Questions, security feedback or benchmark critique? → [Discussions](https://github.com/DamianTodorovic/kepta/discussions)

flowchart LR

subgraph Apps["Your AI apps — every client, one memory"] direction TB A["Claude Desktop · Claude Code"] B["Cursor · Gemini CLI Cline · Codex · Zed"] C["Your scripts"] end subgraph KEPTA["KEPTA — this repository"] direction TB M["MCP server 8 tools · stdio + Streamable HTTP"] G["HTTP API · 32 routes Python client · CLI"] E["Memory engine hybrid retrieval: FTS5 + vectors + graph RRF fusion → local rerank"] end D[("One encrypted file SQLCipher 4 · AES-256 ~/.kepta/kepta.db")] K["OS keychain the key never leaves"] A --> M B --> M C --> G G --> E M --> E E --> D D -.-> K


⚡ One command, every AI client

Needs Node 22.13 or newer (package.json → engines) on the machine you install on; npm has prebuilt SQLite binaries for Node 22, 24 and 26.

npx -y kepta-mcp demo          # six scenes in a throwaway database — nothing of yours is touched

npx -y kepta-mcp setup # connects Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, Gemini CLI, Cline and Roo Code npx -y kepta-mcp remember "Client Miller signs renewals in December." # write a note from the terminal, no AI client needed npx -y kepta-mcp recall "who signs renewals" # read it back: 1 match — ranked by relevance npx -y kepta-mcp stats # size, encryption state, top tags npx -y kepta-mcp timeline "miller" # what was true, and when npx -y kepta-mcp import chatgpt # bring your ChatGPT history with you (export → extract → import)

What those two lines answer, verbatim — kepta-mcp 3.2.0 from the registry on 10.10.2026, a throwaway HOME, an empty memory:

$ npx -y kepta-mcp remember "Client Miller signs renewals in December."

✓ remembered — Client Miller signs renewals in December. type: semantic · id: k-mv2mghs9-fdf75c17

$ npx -y kepta-mcp recall "who signs renewals" 1 match — ranked by relevance

  1. Client Miller signs renewals in December. · semantic · today Client Miller signs renewals in December. #remember

A note is one thing your memory holds — remember writes one by hand, your AI client writes the same kind through the memory_save tool. Then tell your AI something worth keeping — and watch it arrive. Details in the Quick start.



🖥️ Or download the desktop app

The core has no window of its own: its interface is your AI client. If you want a window, that is the free desktop app — same engine, same encrypted file, same key — and it is downloadable from the releases of this repository. For teams and organizations there is KEPTA Enterprise by agreement. These three sentences are the whole answer; every document here says the same.

The app brings the memory browser, hybrid search with retrieval provenance, the knowledge graph, time travel, dossiers and a chat that reads the memory. Download the DMG for your Mac from the latest release (Apple Silicon or Intel) and drag it into Applications. The build is ad-hoc signed and not notarised, so macOS asks a single time. Two ways through, and both work on every macOS version: xattr -dr com.apple.quarantine /Applications/KEPTA.app, or System Settings → Privacy & Security → the KEPTA message → Open Anyway. Once, then never again. Older guides say right-click → *Open*; Apple removed that route in macOS 15 and it does nothing on current systems. (What runs from this repository has no window: npm run dev starts the HTTP API and its POST /mcp — a service on your machine, not an interface.)

The app is free, like everything in this repository. KEPTA Enterprise (team and tenant memory, audit chain, human review, point-in-time recovery) is licensed by agreement — write to me on LinkedIn.

🧠 One engine. Free. For every AI.

KEPTA is not a feature inside one app — it is a memory layer that outlives every model, every app and every context window. Three doors lead into the same encrypted file:

DoorWhat uses it
MCP — 8 tools, stdio (npm binary and container) + Streamable HTTP (this repository, run from source)Every MCP client: Claude, Cursor, Gemini CLI, Cline, Codex, Zed, your own agents
HTTP API — 32 routes, loopback onlyScripts, cron jobs, agent teams, automations
Python — pip install kepta, standard library onlyAny Python project, embedded

Free means free: €0, forever — no account, no licence key, no daily limit, no tier inside the memory, nothing locked to sell you later. The best memory engine we can build is the free one; that is the point. This sentence is about money, not about capacity. On one machine the local API stops accepting new notes once KEPTA_MAX_ACTIVE notes are active (5000 by default, server.ts → maxActiveMemories()): a brake on a runaway agent writing your memory full, not a paywall — raise it with that variable and nothing else changes. Nothing in the free core is a locked feature; see SECURITY.md for every such screw.

Teams and organizations — shared team memory, central policies, MDM, organisation-wide audit — get KEPTA Enterprise by request. Coordination is the only thing we ever charge for; memory quality never is. → write to me on LinkedIn


⚡ Quick start

Connect your AI apps
npx -y kepta-mcp setup

Finds Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, Gemini CLI, Cline and Roo Code on your computer and adds KEPTA to them. It asks per app (--yes connects all of them), keeps a backup of every file it changes and leaves every other entry alone. Zed, Codex CLI and Continue get the exact snippet to paste (their config formats move too fast to write from outside). Any other MCP client:

{

"mcpServers": { "kepta": { "command": "npx", "args": ["-y", "kepta-mcp"] } } }

8 tools: memory_search, memory_save, memory_update, memory_delete, memory_list, memory_graph, memory_consolidate, memory_forget.

HTTP API
git clone https://github.com/DamianTodorovic/kepta.git

cd kepta && npm install && npm run dev

→ http://127.0.0.1:3000

save a note

curl -s localhost:3000/api/memory -H 'Content-Type: application/json' \ -d '{"title":"Client Miller","content":"Billed quarterly.","tags":["client"]}'

search

curl -s "localhost:3000/api/memories/search?q=how+does+miller+pay"

Docker (MCP server only)

Build the image from a clean clone, before any `npm install` — a node_modules built for macOS that ends up in the build context breaks the Linux build (ERR_DLOPEN_FAILED). Measured on this state, 12.10.2026 (docs/belege/r1/kontext-groesse-2128.log.txt): the same folder carries a 180 MB build context, 169 MB of it node_modules, where the tracked files alone are 4 MB. (.dockerignore now keeps node_modules and build artefacts out of the context; until it reaches your checkout, a clean clone is the safe route.)

git clone https://github.com/DamianTodorovic/kepta.git && cd kepta

docker build -t kepta-mcp .

A container has no keychain, so the database key is not optional here: it has

to come from the environment. Generate it ONCE and keep it — it is the only way

back into the volume.

KEPTA_DB_KEY=$(openssl rand -hex 32)

docker run --rm -i -e KEPTA_DB_KEY="$KEPTA_DB_KEY" -v kepta-data:/data kepta-mcp

No key, no file. Pass a real value: 64 hexadecimal characters, openssl rand -hex 32, generated once and stored where you keep your secrets. A container cannot fall back to a keychain, so without KEPTA_DB_KEY a new knowledge base is not created — KEPTA stops with a non-zero exit and says what to do instead. The same value has to come back on every later start: a fresh openssl rand -hex 32 the second time means a key that does not fit the volume, and that also stops with nothing changed. The only way to a plaintext database is the switch that says so out loud, KEPTA_ENCRYPTION=off.

One transitional sentence for whoever reads this against an older build: before this rule was in the code, an unusable value (a placeholder copied out of a guide, too short, not hex) did not fail — KEPTA printed one line, created the database in plaintext and exited 0. If your kepta.db starts with the bytes SQLite format 3, that is what happened, and the file is readable by anyone who can read it. Check the version, then re-key or replace the volume. SECURITY.md has the whole rule.

CI, servers and every other headless start

A CI runner has no keychain either, so the key comes in as a secret — generated once, not per job, or every run starts a fresh empty memory:

# GitHub Actions, one step. The secret holds the 64 hex characters from `openssl rand -hex 32`.
  • run: KEPTA_DB_KEY="${{ secrets.KEPTA_DB_KEY }}" npx -y kepta-mcp stats

Three traps, all measured on this repository:

  • An empty value is not "no key". KEPTA_DB_KEY="" is dropped and the run goes looking in the keychain anyway — on your own machine that means it reads the keychain entry you did not mean to touch. Check that the variable is non-empty before starting, and do not let a templating mistake turn it into "".
  • A placeholder is a value too. Copying a <64-hex>-style token out of any guide is the same case as an empty one.
  • A key in a logged command line is a published key. Pass it through the environment file or the runner's secret mechanism, not through a shell history that CI prints.

If the run cannot reach a key at all, the correct outcome is the one above: no database, a non-zero exit, a sentence naming KEPTA_DB_KEY. A green CI that buil

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