Context7
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Description from the maker (original English)
LLM-maintained personal wiki: cross-references sources, flags contradictions. Local markdown.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
MINDBASE_DATA_DIRYou need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"mindbase": {
"command": "npx",
"args": [
"-y",
"mindbase-mcp"
],
"env": {
"MINDBASE_DATA_DIR": "your-value"
}
}
}
}Run this in your terminal
claude mcp add mindbase --env MINDBASE_DATA_DIR=your-value -- npx -y mindbase-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"mindbase": {
"command": "npx",
"args": [
"-y",
"mindbase-mcp"
],
"env": {
"MINDBASE_DATA_DIR": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"mindbase": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mindbase-mcp"
],
"env": {
"MINDBASE_DATA_DIR": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
MINDBASE_DATA_DIR envThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified with the GitHub account frankchu91, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.3) reached the registry 3 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Context7, Codebase Memory, Exa
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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
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:
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.
Three physical layers on disk (Karpathy's model):
| Layer | Who owns it | What lives there |
|---|---|---|
sources/ | You — append-only, the AI never rewrites it | Quick captures, full notes, PDFs, URLs |
context.md + sources/research/ | The AI — every change human-approved | The maintained wiki: synthesis, concept pages, [[wikilinks]] |
state/ · logs/ · artifacts/ | Derived — always rebuildable | Search 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).
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)
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
| Feature | Claude Code | Cursor / Windsurf / Cline / Continue | Web 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) |
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.
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).
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.
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.
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."