https://github.com/synpulse8-opensource/pulse8-ai-cortex-knowledge-vault

Agent-native knowledge OS built on Markdown. A shared vault for AI agents and humans, backed by a typed knowledge graph, full-text search, and an LLM-powered compiler, all accessible through MCP. Drop files in, let agents read, write, search, link, and compile knowledge. No database required.
https://github.com/synpulse8-opensource/pulse8-ai-cortex-knowledge-vault

ai-agents docker fastapi karpathy-inspired karpathy-llm-wiki knowledge-base knowledge-graph knowledge-management llm llm-wiki markdown mcp python qmd

Last synced: 29 days ago
JSON representation

Host: GitHub
URL: https://github.com/synpulse8-opensource/pulse8-ai-cortex-knowledge-vault
Owner: synpulse8-opensource
License: apache-2.0
Created: 2026-04-24T05:06:17.000Z (2 months ago)
Default Branch: main
Last Pushed: 2026-05-04T21:27:38.000Z (about 2 months ago)
Last Synced: 2026-05-04T21:35:01.112Z (about 2 months ago)
Topics: ai-agents, docker, fastapi, karpathy-inspired, karpathy-llm-wiki, knowledge-base, knowledge-graph, knowledge-management, llm, llm-wiki, markdown, mcp, python, qmd
Language: Python
Homepage: https://www.synpulse8.com/en/our-solutions/pulse8#pulse8-ai
Size: 562 KB
Stars: 1
Watchers: 0
Forks: 1
Open Issues: 0
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE.md

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README

PULSE8.ai Cortex

Agent-native knowledge OS built on Markdown

PULSE8.ai Cortex is an agent-native knowledge OS built on Markdown. It gives AI agents and humans a shared vault backed by a typed knowledge graph, full-text search, and a [MarkItDown](https://github.com/microsoft/markitdown)-powered compiler — all accessible through a unified [MCP](https://modelcontextprotocol.io/) interface.

Drop files in (PDF, DOCX, PPTX, XLSX, HTML, images, and more), let agents read, write, search, link, and compile knowledge — no database required.

> Inspired by [Andrej Karpathy](https://github.com/karpathy)'s [LLM Wiki](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f) pattern — a persistent, compounding knowledge base maintained by LLMs instead of re-derived on every query. Search powered by [Tobi Lütke](https://github.com/tobi)'s [QMD](https://github.com/tobi/qmd).

---

Get started

> [!NOTE]
> PULSE8.ai Cortex requires Docker. An [OpenRouter API key](https://openrouter.ai/keys) is optional — needed only for LLM-powered cross-referencing between wiki articles. File conversion works out of the box without any API key.

1. Clone the repository:
```bash
git clone https://github.com/pulse8-ai/cortex-knowledge-vault.git
cd cortex-knowledge-vault
```
2. Launch PULSE8.ai Cortex:
```bash
./scripts/start.sh
```
This builds and starts both **PULSE8.ai Cortex** (API + MCP on `:8420`) and **QMD** (search on `:3100`), waits for health checks, and you're ready to go.
3. Connect your MCP client (e.g. Claude Desktop) to `http://localhost:8420/mcp/`.

To stop: `./scripts/stop.sh`

### Cortex-only mode (macOS / native QMD)

If you want QMD to run natively (e.g. on macOS with Metal GPU acceleration), start only the Cortex container:

```bash
# Terminal 1: Run QMD natively
npm install -g @tobilu/qmd
VAULT_PATH=./example_vault node docker/qmd/server.mjs

# Terminal 2: Start only Cortex in Docker
./scripts/start.sh --cortex-only
```

To stop: `./scripts/stop.sh --cortex-only`

### GPU-accelerated QMD (EC2 / Linux with NVIDIA GPU)

For production deployments with NVIDIA GPU acceleration:

```bash
docker compose -f docker-compose.yml -f docker-compose.gpu.yml up --build -d
```

See [docs/ec2-gpu-setup.md](docs/ec2-gpu-setup.md) for a full guide on instance selection, NVIDIA toolkit installation, and cost estimates.

Features

| | |
| -------------------- | ------------------------------------------------------------------------------------------------------- |
| **Knowledge Graph** | Typed graph engine (NetworkX) — wikilinks, tags, and custom edges, auto-maintained on every file change |
| **Full-Text Search** | BM25 keyword search via QMD with optional hybrid (vector + reranking) mode |
| **File Compiler** | Converts raw sources (PDF, DOCX, PPTX, XLSX, HTML, images, etc.) to Markdown via [MarkItDown](https://github.com/microsoft/markitdown). LLM used only for cross-referencing. |
| **MCP Server** | Streamable HTTP + stdio transport — works with Claude Desktop, Cursor, and any MCP client |
| **Bulk Ingest** | Ingest dozens or hundreds of files at once from a local directory with SHA-256 dedup and bounded concurrency |
| **REST API** | FastAPI endpoints mirroring all MCP tools at `/api/v1/`, including multipart file upload and bulk ingest |
| **Vault Watcher** | Real-time filesystem monitoring — graph stays in sync automatically |
| **Zero Database** | Everything persists as Markdown + JSON on your filesystem |

MCP tools

| Tool | Description |
| --------------- | ------------------------------------------------------------------ |
| `vault_read` | Read a note by path |
| `vault_write` | Create or update a note |
| `vault_search` | Search the vault (keyword / semantic / hybrid) |
| `vault_link` | Create, query, or delete graph edges |
| `vault_context` | Build a context window: search → graph traversal → ranked subgraph |
| `vault_ingest` | Ingest raw content or binary files (supports `content_base64` for binary) |
| `vault_compile` | Compile unprocessed raw sources into wiki Markdown via MarkItDown |

Architecture

```
┌──────────────────────────────────────────────┐
│ MCP Client (Claude Desktop, Cursor, etc.) │
└──────────┬───────────────────────────────────┘
│ MCP (HTTP or stdio)
┌──────────▼───────────────────────────────────┐
│ PULSE8.ai Cortex :8420 │
│ ┌──────────────────────────────────────┐ │
│ │ Auth (API Key or Microsoft Entra ID) │ │
│ └──────────────┬───────────────────────┘ │
│ ┌─────────┐ ┌──┴───────┐ ┌──────────────┐ │
│ │ MCP │ │ REST API │ │ Vault Watcher│ │
│ │ /mcp/ │ │ /api/v1/ │ │ (watchfiles) │ │
│ └────┬────┘ └────┬─────┘ └──────┬───────┘ │
│ └───────────┼──────────────┘ │
│ ┌──────▼──────┐ │
│ │ Graph Engine│ │
│ │ + Compiler │ │
│ └─────────────┘ │
└──────────┬───────────────────────────────────┘
│
┌──────────▼───────────────────────────────────┐
│ QMD :3100 │
│ BM25 + vector search, auto-indexes on start │
└──────────┬───────────────────────────────────┘
│
┌──────────▼───────────────────────────────────┐
│ Vault (bind-mounted volume) │
│ wiki/ raw/ agents/ sessions/ daily/ │
│ .cortex/ (graph.json, index.md, log.md) │
└──────────────────────────────────────────────┘
```

Bulk ingest

For ingesting many files at once (dozens or hundreds of PDFs, papers, docs), use the one-click shell script instead of feeding them one at a time through MCP. It reads directly from a local directory — no wire overhead, no running server required — deduplicates via SHA-256 hashing, compiles with bounded concurrency, and rebuilds the index once at the end.

### One-click script (recommended)

```bash
# Ingest all files from a directory
./scripts/bulk_ingest.sh ./my-papers/

# Dry-run to preview what would be ingested
./scripts/bulk_ingest.sh ./my-papers/ --dry-run

# Force re-ingest (bypass dedup manifest)
./scripts/bulk_ingest.sh ./my-papers/ --force

# Control LLM concurrency (default: 4)
./scripts/bulk_ingest.sh ./my-papers/ --concurrency 8
```

The script automatically loads your `.env` for the LLM key and vault path, prints a summary, then runs the full pipeline (copy, compile, reindex). No running Cortex server needed.

### Python CLI (direct)

```bash
CORTEX_VAULT_PATH=./example_vault uv run cortex-bulk-ingest --source ./my-papers/
```

### Inside Docker

```bash
# Set INGEST_DIR in .env or export it, then restart
export INGEST_DIR=/path/to/your/papers
docker compose up -d

# Run bulk ingest inside the container
docker exec pulse8-ai-cortex uv run cortex-bulk-ingest --source /ingest
```

### Via REST API

For programmatic use without MCP (requires running Cortex server):

```bash
curl -X POST http://localhost:8420/api/v1/bulk-ingest \
-H "Content-Type: application/json" \
-H "x-api-key: your-secret-api-key" \
-d '{"source_dir": "/ingest", "concurrency": 4}'
```

### Deduplication

The dedup manifest is stored at `.cortex/ingest-manifest.json`. Files are matched by content hash, not filename — renaming a file won't cause re-ingestion, and the same content under a different name will be skipped.

Configuration

Copy the example and fill in your values:

```bash
cp .env.example .env
```

| Variable | Required | Default | Description |
| ------------------------------ | -------- | ------------------------------ | ---------------------------------------------------- |
| `LLM_API_KEY` | No | — | OpenRouter (or compatible) API key (for cross-referencing only) |
| `COMPILER_MODEL` | No | `anthropic/claude-sonnet-4` | Model for cross-reference detection |
| `LLM_BASE_URL` | No | `https://openrouter.ai/api/v1` | LLM API base URL |
| `VAULT_DIR` | No | `./example_vault` | Path to your vault directory |
| `INGEST_DIR` | No | `./ingest` | Path to bulk-ingest source directory (mounted as `/ingest` in Docker) |
| `QMD_REFRESH_INTERVAL_SECONDS` | No | `900` | Periodic re-index interval (seconds; `0` to disable) |
| `QMD_EMBED_TIMEOUT_MS` | No | `600000` | Embed timeout in ms (increase for CPU-only deployments) |
| `QMD_URL` | No | — | External QMD URL for cortex-only mode (e.g. `http://host.docker.internal:3100`) |
| `AUTH_METHOD` | No | `none` | Authentication method: `none`, `apikey`, or `oidc` (see [Authentication](#authentication)) |
| `API_KEY` | No | — | Static API key for `x-api-key` header (used when `AUTH_METHOD=apikey`) |
| `OIDC_TENANT_ID` | No | — | Microsoft Entra ID tenant ID (used when `AUTH_METHOD=oidc`) |
| `OIDC_CLIENT_ID` | No | — | Microsoft Entra ID app (client) ID |
| `OIDC_CLIENT_SECRET` | No | — | Microsoft Entra ID client secret |
| `OIDC_BASE_URL` | No | `http://localhost:8420` | Public base URL of the Cortex server (used for OAuth callbacks) |

`OPENROUTER_API_KEY` and `CORTEX_LLM_API_KEY` are accepted as aliases for `LLM_API_KEY`.

Authentication

Cortex supports two authentication methods that protect both the REST API (`/api/v1/`) and the MCP endpoint (`/mcp/`). Set `AUTH_METHOD` in `.env` to choose:

| `AUTH_METHOD` | Description |
| ------------- | ----------- |
| `none` | Default. All endpoints are open — no authentication required. |
| `apikey` | Static API key. Clients pass `x-api-key` header. |
| `oidc` | Microsoft Entra ID (Azure AD) with OAuth 2.0 + MFA support. |

### API Key (`AUTH_METHOD=apikey`)

The simplest option. Set the method and key in `.env`:

```
AUTH_METHOD=apikey
API_KEY=your-secret-api-key
```

Clients pass it via the `x-api-key` header:

```bash
# REST API
curl http://localhost:8420/api/v1/health \
-H "x-api-key: your-secret-api-key"

# MCP (via curl)
curl -X POST http://localhost:8420/mcp/ \
-H "x-api-key: your-secret-api-key" \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{...}}'
```

No OAuth discovery endpoints are served — no login popups. Requests without a valid key receive a `401`.

### Microsoft Entra ID (`AUTH_METHOD=oidc`)

For enterprise environments that require interactive login with MFA support:

```
AUTH_METHOD=oidc
OIDC_TENANT_ID=your-tenant-id
OIDC_CLIENT_ID=your-client-id
OIDC_CLIENT_SECRET=your-client-secret
OIDC_BASE_URL=http://localhost:8420
```

This enables:
- **REST API**: OAuth 2.0 Authorization Code Flow via `GET /api/v1/login`. After login, pass the access token as `Authorization: Bearer `. A valid `x-api-key` header is also accepted as a fallback when `API_KEY` is set.
- **MCP endpoint**: FastMCP's built-in OIDCProxy handles interactive browser-based login.

### Azure AD app registration

To use OIDC, register an app in the [Azure Portal](https://portal.azure.com):

1. Go to **Azure Active Directory → App registrations → New registration**
2. Set the redirect URI to `http://localhost:8420/api/v1/auth/callback` (Web platform)
3. Under **Certificates & secrets**, create a client secret
4. Under **API permissions**, add `openid`, `profile`, and `email` (Microsoft Graph → Delegated)
5. Copy the Tenant ID, Client ID, and Client Secret into `.env`

MCP client setup

### Claude Desktop

An example config is included at `[claude_desktop_config.example.json](claude_desktop_config.example.json)`.

**HTTP with API key (recommended)** — PULSE8.ai Cortex runs as a persistent server:

```json
{
"mcpServers": {
"cortex": {
"url": "http://localhost:8420/mcp/",
"headers": {
"x-api-key": "your-secret-api-key"
}
}
}
}
```

**HTTP without auth** — when no authentication is configured:

```json
{
"mcpServers": {
"cortex": {
"url": "http://localhost:8420/mcp/"
}
}
}
```

**Stdio** — Claude Desktop launches the server on demand (no auth needed):

```json
{
"mcpServers": {
"cortex": {
"command": "uv",
"args": ["run", "--project", "/path/to/cortex", "python", "-m", "cortex.mcp"],
"env": {
"CORTEX_VAULT_PATH": "/path/to/your/vault"
}
}
}
}
```

### Cursor

Add to your `.cursor/mcp.json`:

```json
{
"mcpServers": {
"cortex": {
"url": "http://localhost:8420/mcp/",
"headers": {
"x-api-key": "your-secret-api-key"
}
}
}
}
```

How it works

**Watcher** and **Compiler** are independent components:

- The **Watcher** maintains the graph. Any `.md` file added, modified, or deleted triggers automatic node/edge updates.
- The **Compiler** converts raw source files to Markdown using [MarkItDown](https://github.com/microsoft/markitdown) and writes them to `wiki/`. Supported formats include PDF, DOCX, PPTX, XLSX, HTML, CSV, JSON, XML, images (EXIF/OCR), and plain text. The LLM is only used for optional cross-reference detection between articles.

They connect indirectly: the compiler writes to `wiki/`, the watcher picks those up and updates the graph.

### Supported file formats

| Format | Extensions |
| ------ | ---------- |
| PDF | `.pdf` |
| Microsoft Word | `.docx` |
| Microsoft PowerPoint | `.pptx` |
| Microsoft Excel | `.xlsx`, `.xls` |
| HTML | `.html`, `.htm` |
| Text-based | `.csv`, `.json`, `.xml`, `.txt`, `.md` |
| Images | `.jpg`, `.png`, etc. (EXIF metadata) |

**Search** uses a two-stage pipeline:

1. **QMD** performs keyword/semantic search on file contents
2. **PULSE8.ai Cortex** enriches results with graph edges (wikilinks, tags, relationships between matched notes)

QMD answers *"what's relevant?"* — the graph answers *"how are these results connected?"*

Development

```bash
# Install dependencies
uv sync --all-extras

# Run tests
uv run pytest tests/ -v

# Run shell tests (requires bats-core)
bats tests/test_start_sh.bats

# Start PULSE8.ai Cortex locally (without Docker)
CORTEX_MCP_TRANSPORT=http CORTEX_VAULT_PATH=./example_vault uv run python scripts/serve.py
```

### Utility scripts

| Script | Description |
| ------------------------- | -------------------------------------------------------------- |
| `scripts/serve.py` | Dev server (HTTP or stdio based on `CORTEX_MCP_TRANSPORT`) |
| `scripts/compile.py` | Batch-compile all raw sources |
| `scripts/reindex.py` | Full reindex + graph rebuild |
| `scripts/bulk_ingest.sh` | One-click bulk ingest from a local directory |
| `scripts/bulk_ingest.py` | Python CLI for bulk ingest (called by `bulk_ingest.sh`) |
| `scripts/lint.py` | Lint vault structure |

Data persistence

The vault directory is bind-mounted from your host into the containers. All data lives on your local disk and survives container restarts.

The QMD search index is stored in a Docker volume (`qmd-cache`). To force a full re-index:

```bash
docker compose down -v
./scripts/start.sh
```

Contributing

We welcome contributions! Please open an issue to discuss your idea before submitting a pull request.

```bash
# Fork and clone the repo
git clone https://github.com//cortex-knowledge-vault.git
cd cortex-knowledge-vault

# Create a branch
git checkout -b feat/my-feature

# Install dev dependencies
uv sync --all-extras

# Make changes, then run tests
uv run pytest tests/ -v

# Submit a pull request
```

Reporting issues

Use [GitHub Issues](https://github.com/pulse8-ai/cortex-knowledge-vault/issues) to report bugs or request features.

Acknowledgements

PULSE8.ai Cortex builds on ideas and tools from the open-source community:

- **[LLM Wiki](https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f)** by [Andrej Karpathy](https://github.com/karpathy) — the core pattern of an LLM-maintained, persistent knowledge base that compiles and interlinks knowledge incrementally rather than re-discovering it from raw documents on every query. This gist is the direct inspiration for Cortex's architecture.
- **[QMD](https://github.com/tobi/qmd)** by [Tobi Lütke](https://github.com/tobi) — the on-device search engine powering all full-text and hybrid search in Cortex. QMD combines BM25, vector search, and LLM re-ranking, all running locally.
- **[MarkItDown](https://github.com/microsoft/markitdown)** by [Microsoft](https://github.com/microsoft) — the file-to-Markdown converter powering the Cortex compiler. Converts PDF, Office documents, HTML, images, and more into structured Markdown for ingestion into the vault.

## License

This project is licensed under the [PULSE8.ai Cortex Open Source License](LICENSE.md) (Apache License 2.0 with additional terms).

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