<p align="center">
<img src="https://img.shields.io/badge/rust-1.88+-orange?logo=rust" alt="Rust 1.88+">
<img src="https://img.shields.io/badge/license-MIT-blue" alt="MIT License">
<img src="https://img.shields.io/badge/platform-linux%20%7C%20macos%20%7C%20windows-lightgrey" alt="Platform">
</p>
<h1 align="center">kdex</h1>
<p align="center">
<strong>All your knowledge. One search. AI-ready.</strong>
</p>
<p align="center">
Index your code, docs, notes, and wikis locally.<br>
Let AI assistants search everything you know.
</p>
---
## The Problem
You have knowledge everywhere:
- **Code** across dozens of repositories
- **Notes** in Obsidian, Logseq, or markdown files
- **Docs** scattered in wikis and READMEs
When you ask an AI assistant for help, it has no idea what's in YOUR files. You end up copy-pasting context manually.
## The Solution
```bash
# Index everything
kdex index ~/code/my-project
kdex index ~/Documents/obsidian-vault
kdex index ~/wiki
# Search instantly
kdex search "how to deploy"
# AI assistants can now search your knowledge
kdex mcp # Start MCP server for Copilot, Claude, Ollama
```
**kdex** creates a local search index that AI tools can query. Your data never leaves your machine.
---
## ✨ Features
| 🔍 **Instant Search** | SQLite FTS5 gives sub-millisecond full-text search |
| 🤖 **AI-Ready** | MCP server for GitHub Copilot, Claude, Ollama |
| 📁 **Universal** | Code repos, Obsidian vaults, wikis, any markdown |
| 🔒 **Local-First** | Your data stays on your machine. Always. |
| ⚡ **Fast** | Index 100k files in seconds, search in milliseconds |
| 🌐 **Remote Repos** | Add GitHub repos by URL—auto-cloned, auto-synced |
| 📦 **Portable** | Export/import config for easy machine migration |
| 🖥️ **Interactive TUI** | Full-screen interface with preview panel |
---
## 🚀 Quickstart
```bash
# Install
cargo install kdex
# Index your project
kdex index .
# Add a GitHub repo
kdex add --remote owner/repo
# Search (just type your query!)
kdex "authentication"
# Launch interactive mode
kdex
```
That's it. Your knowledge, instantly searchable.
---
## 🤖 AI Integration
kdex speaks [MCP](https://modelcontextprotocol.io/) (Model Context Protocol), so AI assistants can search your indexed content directly.
### GitHub Copilot CLI
Add to `~/.config/github-copilot/mcp.json`:
```json
{
"mcpServers": {
"kdex": { "command": "kdex", "args": ["mcp"] }
}
}
```
### Claude Desktop
Add to `~/.config/claude/claude_desktop_config.json`:
```json
{
"mcpServers": {
"kdex": { "command": "kdex", "args": ["mcp"] }
}
}
```
### Ollama (Local LLMs)
Pipe search results to your local model:
```bash
ollama run llama3 "Explain this code:"
```
See [MCP Integration Guide](doc/mcp-integration.md) for more details.
---
## 📖 What It Indexes
| **Code Repositories** | Any git repo, monorepos, microservices |
| **Knowledge Bases** | Obsidian vaults, Logseq graphs, Dendron |
| **Documentation** | Markdown wikis, READMEs, technical docs |
| **Config Files** | YAML, TOML, JSON with searchable content |
kdex respects `.gitignore` and skips binary files automatically.
---
## 💻 Usage
### Interactive Mode (TUI)
```bash
kdex
```
Full-screen interface with:
- Real-time search as you type
- File preview panel (`Ctrl+P`)
- Repository management
- Keyboard-driven navigation
### Command Line
```bash
kdex index <path> # Index a directory
kdex search <query> # Search indexed content
kdex search <query> --json # JSON output for scripting
kdex list # List indexed repositories
kdex remove <path> # Remove from index
kdex mcp # Start MCP server
```
Run `kdex --help` for all options.
---
## 🔧 Installation
### From crates.io (recommended)
```bash
cargo install kdex
```
### From source
```bash
git clone https://github.com/urbanisierung/kdex.git
cd kdex
cargo install --path .
```
### Requirements
- Rust 1.88+ ([install via rustup](https://rustup.rs/))
- Works on Linux, macOS (Apple Silicon), and Windows
---
## 📚 Documentation
- [Features](doc/features.md) — Full feature list
- [Documentation](doc/documentation.md) — Detailed usage guide
- [MCP Integration](doc/mcp-integration.md) — AI assistant setup
- [Ollama Integration](doc/ollama-integration.md) — Local LLM workflow
- [Roadmap](doc/roadmap.md) — What's coming next
---
## 🛠️ Development
```bash
make ci # Run full CI pipeline (Docker)
make ci-quick # Quick checks (format + clippy)
make test # Run tests
make build # Build debug binary
```
See [CONTRIBUTING.md](CONTRIBUTING.md) for development setup.
---
## License
MIT © [urbanisierung](https://github.com/urbanisierung)