Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
LLM-maintained personal wiki: cross-references sources, flags contradictions. Local markdown.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
MINDBASE_DATA_DIRNecesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"mindbase": {
"command": "npx",
"args": [
"-y",
"mindbase-mcp"
],
"env": {
"MINDBASE_DATA_DIR": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add mindbase --env MINDBASE_DATA_DIR=your-value -- npx -y mindbase-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"mindbase": {
"command": "npx",
"args": [
"-y",
"mindbase-mcp"
],
"env": {
"MINDBASE_DATA_DIR": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"mindbase": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"mindbase-mcp"
],
"env": {
"MINDBASE_DATA_DIR": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
MINDBASE_DATA_DIR envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub frankchu91, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.1.3) llegó al registro hace 3 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Node.js en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
Up-to-date docs for AI agents
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.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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."