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

Mindbase

作者:frankchu91版本 0.1.3i★ –i在你的电脑上运行
注册名称io.github.frankchu91/mindbase

安装

概览

作者提供的说明(英文原文)

LLM-maintained personal wiki: cross-references sources, flags contradictions. Local markdown.

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

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": {
    "mindbase": {
      "command": "npx",
      "args": [
        "-y",
        "mindbase-mcp"
      ],
      "env": {
        "MINDBASE_DATA_DIR": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add mindbase --env MINDBASE_DATA_DIR=your-value -- npx -y mindbase-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": {
    "mindbase": {
      "command": "npx",
      "args": [
        "-y",
        "mindbase-mcp"
      ],
      "env": {
        "MINDBASE_DATA_DIR": "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": {
    "mindbase": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "mindbase-mcp"
      ],
      "env": {
        "MINDBASE_DATA_DIR": "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

  • MINDBASE_DATA_DIR env
    Data directory for projects and wiki files (default: ~/mindbase-data)

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 frankchu91 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 7241 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 7241 个服务器的 25% 更新
  • 基础检查结果等于或优于此分类中其他 7241 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

Mindbase 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 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★ 64,224MIT3天前更新
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★ 5,213MIT44天前更新
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。

MindBase — Karpathy's LLM Wiki, as a product

An open-source implementation of Andrej Karpathy's LLM Wiki idea: an AI that builds and maintains a wiki from your sources. Not RAG-in-a-vector-DB. A real markdown wiki on your disk, that an LLM gardens for you between conversations.

npx mindbase-app

One command: starts the local server, opens the web app, and walks you through picking a free local model that fits your RAM. No API key, nothing leaves your machine. (Node 20+)

MindBase implements Andrej Karpathy's LLM-Wiki pattern: you feed it sources (papers, articles, thoughts); the LLM reads, cross-references, flags contradictions, and writes structured wiki pages. Later, when you ask a question, the wiki already has the synthesized answer — no vector-search re-derivation at query time.

Status: Early access, actively developed. What's new: CHANGELOG · Releases


Why MindBase

You read a lot. Papers, articles, tweets, docs. You want to remember them, connect them, form opinions from them. Today you have two bad options:

  • Notion / Obsidian / Roam: Passive containers. You do all the organizing. AI features are bolted-on generation, not maintenance.
  • NotebookLM / Perplexity Pages / ChatGPT search: RAG-based. Nothing accumulates. Every question re-derives the answer from raw sources.

MindBase is the third option: the LLM actively maintains a persistent, structured wiki as you feed it sources. Knowledge compounds. Your context.md gets sharper every time you contribute. The AI *remembers you across sessions* because your beliefs are written down in markdown files — not stored in a chat history that gets summarized away.

Think of it as a personal Wikipedia that an AI intern writes for you, kept up to date, cross-referenced, and honest about what it doesn't know.

How it works (30 seconds)

Three physical layers on disk (Karpathy's model):

LayerWho owns itWhat lives there
sources/You — append-only, the AI never rewrites itQuick captures, full notes, PDFs, URLs
context.md + sources/research/The AI — every change human-approvedThe maintained wiki: synthesis, concept pages, [[wikilinks]]
state/ · logs/ · artifacts/Derived — always rebuildableSearch index, snapshots, lint findings, op history

Three operations run the loop: ingest (AI reads a source, discusses takeaways, you approve the wiki updates), build (regenerate context.md from everything unbuilt), lint (the AI audits its own wiki for contradictions, stale claims, and orphans).

What makes it different

  • The AI asks before writing. Every ingest shows takeaways + a checkbox plan; only what you approve gets written. No black-box edits to your knowledge.
  • You can watch the wiki absorb your notes. Every note carries a status chip — ✨ *Add to wiki* until digested, ✓ *In wiki* after.
  • It audits its own knowledge. One command re-reads the whole wiki and reports contradictions with the exact conflicting sentences quoted. Notion and NotebookLM structurally cannot do this.
  • Free and local by default. Hardware-detect wizard installs the best Ollama model for your RAM. Cloud keys optional.
  • Plain markdown on disk. Grep it, git it, open it in Obsidian, leave anytime.

Install

Browser (fastest): npx mindbase-app — shown above. Everything runs locally at localhost:4321.

Claude Code (flagship): the full Karpathy 8-step ingest with sub-agents, slash commands, and per-agent tool boundaries:

/plugin marketplace add frankchu91/mindbase-llm-wiki

/plugin install mb@mindbase

Restart when prompted, then type / — you should see /mb:contribute, /mb:build, /mb:ask, /mb:lint and 8 more. You get 5 sub-agents with strict tool allowlists (the builder has no file-write tool at all — only an atomic-write MCP call), plus a SessionStart hook that auto-injects your project context.

Cursor

Add to ~/.cursor/mcp.json:

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

Restart Cursor — the tool picker should list mindbase_contribute and 48 others. Recommended: add a conventions block to ~/.cursor/rules.md so the LLM reliably routes "add to mindbase X" to the tools — copy it from the guide.

Windsurf

Cascade settings → MCP → add:

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

Same rules-file approach as Cursor works for Cascade.

Cline (VSCode)

Cline settings → MCP Servers:

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

Cline auto-detects; every tool call gets a confirmation dialog by default.

Continue.dev

~/.continue/config.json, under experimental.modelContextProtocolServers:

{ "experimental": { "modelContextProtocolServers": [ { "transport": { "type": "stdio", "command": "npx", "args": ["-y", "mindbase-mcp"] } } ] } }

MCP tools appear under @ in chat.

Any other MCP client (Zed, Aider, Goose, Claude Agent SDK…)

Point it at npx -y mindbase-mcp as a stdio server. See your client's MCP docs for the config location.

Next: create your first project and learn the four daily workflows in the [Guide →](docs/guide.md)

The web UI

Since 0.3 the browser app stands on its own — write notes in a full WYSIWYG editor (Cmd+N), quick-capture from anywhere (Cmd+I), and run the AI operations with approval cards: /contribute, /build, /lint, /research. Live demos on the [website](https://frankchu91.github.io/mindbase-llm-wiki/).

Free local models: the setup wizard detects your hardware and installs what fits — llama3.2:3b (8GB), qwen3:14b (24GB+), or Meta's Muse Glimmer 30B (32GB+ Apple Silicon, Ollama ≥ 0.32.7). Measured guidance: qwen3:14b for interactive work (~30s), Glimmer for background lint/build — slower, but its findings quote the exact conflicting sentences. The model switcher on the chat composer flips between them in two clicks.

Feature matrix by editor

FeatureClaude CodeCursor / Windsurf / Cline / ContinueWeb UI
Slash commands (/mb:*)✅❌ (use natural language)✅ (/contribute, /build, /lint, /research)
MCP tools directly✅✅❌
Karpathy 8-step ingest with approval✅ (sub-agents)⚠️ Manual via prompt✅ (approval cards)
Contribute / ingest PDF & URL✅✅✅ (upload + ✨ Process)
Ask wiki with cited answers✅✅✅
Build / health check✅✅✅
Wiki tree browsing + rich editor❌❌✅
-p project-id routing✅⚠️ natural language✅ (switcher)

Where your data lives

Everything is plain markdown under ~/mindbase-data/ (override: MINDBASE_DATA_DIR):

~/mindbase-data/projects/my-research/

├── README.md # Ops manual — you edit, LLM reads ├── context.md # Synthesized truth — LLM writes, you approve ├── index.yaml # Auto-generated catalog ├── sources/ │ ├── contributors/ / # Your dated entries + notes (append-only) │ ├── research/ # LLM-authored wiki pages │ └── raw/ # PDFs, HTML captures ├── logs/ # Chronological operation log ├── artifacts/ # Briefs, exports, lint findings └── state/builder/snapshots/ # context.md snapshots for rollback

No proprietary database — what you see on disk is what MindBase knows. git init it, back it up with anything, delete a project with rm -rf.

Architecture at a glance

 Claude Code / Cursor / any MCP editor          Web UI (npx mindbase-app)

│ MCP · sub-agents with │ /commands · │ per-agent tool allowlists │ approval cards └─────────────┬─────────────────────────┬──────┘ ▼ ▼ ┌──────────────────────────────────────────────┐ │ One ops engine: gather context → single │ │ constrained JSON completion → human │ │ approval → whitelisted executors → log │ └─────────────────────┬────────────────────────┘ ▼ ~/mindbase-data/ · plain markdown (LLM: Ollama local models or any cloud key)

Monorepo: packages/core (TS strict library) · apps/mcp (49-tool MCP server) · apps/server + apps/web (Express + React UI) · apps/app (npx launcher) · apps/plugin (Claude Code bundle).

Docs & help

  • [Guide](docs/guide.md) — first project, the four daily workflows, multi-project routing, troubleshooting
  • [Website](https://frankchu91.github.io/mindbase-llm-wiki/) — live demos
  • [CHANGELOG](CHANGELOG.md) · [Issues](https://github.com/frankchu91/mindbase-llm-wiki/issues) — I reply to every issue same-day during beta
  • The idea: Karpathy's LLM Wiki gist

Roadmap

Next: browser extension for one-click page capture · audio input via Whisper · unified meta-tool for Cursor/Windsurf slash-like UX. Later: team projects with human-in-the-loop review · audio digests · desktop app · mobile capture.

Feedback

Beta through 2026-Q4. If you tried MindBase and gave up — please tell me why: issues or haobing0304@gmail.com. The blockers you hit are gold.

License

MIT — do what you want, no warranty. If you build something interesting on top, I'd love to hear about it.


Built with the belief that AI's most valuable gift is not "generation on demand" but "gardening of a persistent artifact you own."

问 PopNx