# Semantic Search
Semantic search over markdown files. Find related notes by meaning, not just keywords. Detect duplicates before creating new notes.
Supports two server modes:
- **MCP mode** — For Claude Code integration
- **REST mode** — For OpenClaw, scripts, and HTTP clients
## Features
- Semantic search using sentence-transformers
- Duplicate/similar note detection
- Auto-updating index with file watcher
- Multi-directory support
- Inline tag extraction (`#tag-name`)
## Installation
### Permanent install (recommended)
```bash
# Install as a tool (creates ~/.local/bin/semantic-search-mcp)
uv tool install git+https://github.com/bborbe/semantic-search
```
> **💡 No GPU? Use CPU-only PyTorch**
>
> The default install includes CUDA support (~7GB). If you don't have a dedicated GPU, install with CPU-only PyTorch to save ~5GB disk space:
>
> ```bash
> uv tool install --index https://download.pytorch.org/whl/cpu \
> git+https://github.com/bborbe/semantic-search
> ```
>
> Performance is identical for typical vault sizes — embedding models run fine on CPU.
### One-off usage
```bash
# Run directly with uvx (no install needed)
uvx --from git+https://github.com/bborbe/semantic-search semantic-search-mcp serve
```
### From PyPI (when published)
```bash
pip install semantic-search-mcp
```
## Server Modes
### MCP Mode (for Claude Code)
```bash
claude mcp add -s project semantic-search \
--env CONTENT_PATH=/path/to/vault \
-- \
uvx --from git+https://github.com/bborbe/semantic-search semantic-search-mcp serve
```
**Tools available:**
- `search_related(query, top_k=5)` — Find semantically related notes
- `check_duplicates(file_path)` — Detect duplicate/similar notes
### REST Mode (for OpenClaw/HTTP)
```bash
# Start server
CONTENT_PATH=/path/to/vault semantic-search-mcp serve --mode rest --port 8321
# Or with uvx
CONTENT_PATH=/path/to/vault uvx --from git+https://github.com/bborbe/semantic-search \
semantic-search-mcp serve --mode rest --port 8321
```
**Endpoints:**
| Endpoint | Method | Description |
|----------|--------|-------------|
| `/search?q=...&top_k=5` | GET | Semantic search |
| `/duplicates?file=...&threshold=0.85` | GET | Find duplicate notes |
| `/health` | GET | Health check with index stats |
| `/reindex` | GET/POST | Force index rebuild |
**Example queries:**
```bash
# Search
curl 'http://localhost:8321/search?q=kubernetes+deployment'
# Find duplicates
curl 'http://localhost:8321/duplicates?file=notes/my-note.md'
# Health check
curl 'http://localhost:8321/health'
```
## CLI Commands
One-shot commands without running a server:
```bash
# Search
CONTENT_PATH=/path/to/vault semantic-search-mcp search "kubernetes deployment"
# Find duplicates
CONTENT_PATH=/path/to/vault semantic-search-mcp duplicates path/to/note.md
```
## Configuration
### Environment Variables
| Variable | Description | Default |
|----------|-------------|---------|
| `CONTENT_PATH` | Directory to index (comma-separated for multiple) | `./content` |
| `LOG_LEVEL` | Logging level (DEBUG, INFO, WARNING, ERROR) | `INFO` |
### Multiple Directories
Index multiple directories by separating paths with commas:
```bash
CONTENT_PATH=/path/to/vault1,/path/to/vault2,/path/to/docs
```
All directories are indexed together and searched as one unified index.
## How It Works
First run downloads a small embedding model (~90MB) and indexes your markdown files (<1s for typical vaults). The index auto-updates when files change via filesystem watcher.
### Indexed Content
Each markdown file is indexed with weighted components:
| Component | Weight | Notes |
|-----------|--------|-------|
| Filename | 3x | |
| Frontmatter `title` | 3x | |
| Frontmatter `tags` | 2x | Merged with inline tags |
| Frontmatter `aliases` | 2x | |
| Inline tags (`#tag`) | 2x | Extracted from body |
| First H1 heading | 2x | |
| Body content | 1x | First 500 words |
## Development
```bash
# Clone
git clone https://github.com/bborbe/semantic-search
cd semantic-search
# Install dev dependencies
make install
# Run checks
make check
# Run tests
make test
```
## License
BSD 2-Clause License — see [LICENSE](LICENSE).
