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.
git clone https://github.com/egorfedorov/mozg{
"mcpServers": {
"mozg": {
"command": "node",
"args": ["/path/to/mozg/dist/index.js"]
}
}
}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)
[](https://github.com/egorfedorov/mozg/actions)
[](https://mozg.sh)
[](https://learn.mozg.sh)
[](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.
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.
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