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Exam-scored knowledge brains for AI agents: paste a docs URL, get a searchable brain over MCP with a measured score and known gaps. AGPL.

MCP ServersOfficial Registry5 stars1 forksTypeScriptAGPL-3.0Updated today
Install in Claude Code / Claude Desktop
Method: Manual
Claude Code CLI
git clone https://github.com/egorfedorov/mozg
claude_desktop_config.json (Claude Desktop)
{
  "mcpServers": {
    "mozg": {
      "command": "node",
      "args": ["/path/to/mozg/dist/index.js"]
    }
  }
}
1. Run the command above in your terminal (Claude Code), or paste the JSON config into claude_desktop_config.json (Claude Desktop).
2. Replace any <placeholder> values with your API keys or paths.
3. Restart Claude. The MCP server and its tools appear automatically.
💡 Clone https://github.com/egorfedorov/mozg and follow its README for install instructions.
Use cases

MCP Servers overview

<div align="center">

<img src="public/brand/devto-cover.jpg" alt="mozg — a brain assembled from notes, stamped with a passing grade" width="720" />

# mozg.

**Exam-scored knowledge brains for AI coding agents.**
Paste one docs URL → get a searchable brain your agent queries over MCP —
with a measured score and a public list of what it does *not* know.

[![License: AGPL-3.0](https://img.shields.io/badge/license-AGPL--3.0-14161a)](LICENSE)
[![CI](https://github.com/egorfedorov/mozg/actions/workflows/ci.yml/badge.svg)](https://github.com/egorfedorov/mozg/actions)
[![Cloud](https://img.shields.io/badge/cloud-mozg.sh-f15060)](https://mozg.sh)
[![Learn](https://img.shields.io/badge/humans-learn.mozg.sh-3ec300)](https://learn.mozg.sh)
[![MCP](https://img.shields.io/badge/protocol-MCP-14161a)](https://mozg.sh/connect)

[Start here](https://mozg.sh/start) · [Catalogue](https://mozg.sh/explore) ·
[Why not a context file](https://mozg.sh/vs) · [Self-host guide](docs/SELFHOST.md) · [Roadmap](docs/ROADMAP.md)

</div>

---

Your agent answers from memory, and memory has a date on it. Context files
rot silently, cost tokens on every session, and can never tell you what they
actually cover. mozg is built on one mechanism applied everywhere:

> **Knowledge must be measured.**

<p align="center">
  <img src="public/brand/demo.svg" alt="Terminal: connecting mozg to Claude Code, then an agent answering an Expo question from the brain with a cited source and exam score" width="820" />
</p>

## The loop

```mermaid
flowchart LR
    A[one docs URL] --> B[crawler<br/>github tree · llms.txt · sitemap]
    B --> C[atomic notes<br/>+ embeddings]
    C --> D{{the exam<br/>~30 questions from the goal}}
    D -->|score + failed questions| E[focused re-read<br/>chases the gaps]
    E --> C
    F[agents querying over MCP] -->|zero-hit searches| D
    F -->|corrections| G[owner review] --> C
```

- **The exam is the product.** The brain's goal becomes control questions,
  re-sat after every ingest. *Trained 92%* is a fact, not a claim — and the
  failures are listed publicly, so agents are told the gaps before they
  search. Anti-bluff questions verify it refuses what it doesn't know.
- **Zero-context search.** Retrieval is server-side (hybrid + reranker).
  A brain can hold 3,000 notes; an answer costs the three it needed.
- **The collective mind.** A search that returns nothing becomes an exam
  question. Corrections agents file become owner-reviewed notes. Nothing is
  ever deleted — every version is kept, and the diff between sittings shows
  on the brain's page.
- **learn.** Any brain doubles as a spaced-repetition course for humans at
  [learn.mozg.sh](https://learn.mozg.sh) — read → recall → quiz, streaks, a
  certificate at 80%, and a scoreboard against your own agent.
- **Injection-hardened.** Published notes are scanned for credential leaks,
  PII and prompt-injection language; third-party notes arrive framed as
  data, not instructions; AI training crawlers are refused in robots.txt.

## Run your own, in one command

```bash
git clone https://github.com/egorfedorov/mozg.git && cd mozg
cp .env.selfhost.example .env     # fill ANTHROPIC_API_KEY + BETTER_AUTH_SECRET
docker compose -f docker-compose.selfhost.yml up
```

Postgres with pgvector, the embedder, the app and the worker come up
together; the schema migrates itself before the app starts. Open
**http://localhost:3300**, create an account, paste a docs URL.

First boot downloads ~2.2 GB of embedding weights into a volume — that is the
slow part, and it happens once. Full operational detail, including production
deploys behind nginx, lives in [docs/SELFHOST.md](docs/SELFHOST.md).

## Cloud, or your own metal

| | [mozg.sh](https://mozg.sh) cloud | self-host (this repo) |
|---|---|---|
| Read, connect, study | free | yours |
| Official catalogue | free, curated, kept current | seed it yourself (`scripts/catalogue.ts`) |
| Build brains | free trial brain, then plans **or bring your own API key** | your keys, no limits |
| Marketplace | outside authors sell, 95% to them | n/a |
| Ops | ours | [`docs/SELFHOST.md`](docs/SELFHOST.md) |

The deal is honest: building brains spends model tokens. On the cloud you
either pay a plan (we spend), set your own API key in settings (you spend),
or teach through a Claude Code subscription with the plugin's `/mozg:train`.

## Stack

Next.js 16 · Postgres 14 + pgvector (HNSW) · pg-boss (queue in Postgres) ·
better-auth · bge-m3 embeddings + bge-reranker (self-hosted FastAPI) ·
Playwright render service for JS-shell docs sites · esbuild-bundled worker.
178 tests, CI on every push.

## Contributing

Bug reports with reproduction beat everything; `brain_feedback` reports from
real use beat those. Small PRs welcome — see [CONTRIBUTING.md](CONTRIBUTING.md).
New catalogue packs are data entries, not code.

## License

[AGPL-3.0](LICENSE). Run it, change it, self-host it; host it for others and
your changes stay open. The hosted cloud at mozg.sh sells convenience and
inference — never locks.
ai-agentsclaudedeveloper-toolsknowledge-basellmmcpmodel-context-protocolragself-hostedspaced-repetition

What people ask about mozg

What is egorfedorov/mozg?

+

egorfedorov/mozg is mcp servers for the Claude AI ecosystem. Exam-scored knowledge brains for AI agents: paste a docs URL, get a searchable brain over MCP with a measured score and known gaps. AGPL. It has 5 GitHub stars and was last updated today.

How do I install mozg?

+

You can install mozg by cloning the repository (https://github.com/egorfedorov/mozg) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.

Is egorfedorov/mozg safe to use?

+

egorfedorov/mozg has not been audited yet by our security agent. Review the original repository on GitHub before using it in production.

Who maintains egorfedorov/mozg?

+

egorfedorov/mozg is maintained by egorfedorov. The last recorded GitHub activity is from today, with 0 open issues.

Are there alternatives to mozg?

+

Yes. On ClaudeWave you can browse similar mcp servers at /categories/mcp, sorted by popularity or recent activity.

Deploy mozg to your cloud

Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.

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