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# Getting Started

## System requirements

Section titled “System requirements”

- Python 3.11+ (tested on 3.11, 3.12, 3.13)
- A C compiler and `cmake` (needed to build tree-sitter grammars)

Platform | Setup
--- | ---
macOS | `xcode-select --install`
Ubuntu/Debian | `sudo apt install build-essential cmake`
Fedora/RHEL | `sudo dnf install gcc gcc-c++ cmake`
Windows | Visual Studio Build Tools (C++ workload) + CMake

## Install

Section titled “Install”

CCE needs an embedding backend to index your code. Pick one:

Option | Install command | What it needs
--- | --- | ---
Local (recommended) | `uv tool install "code-context-engine[local]"` | Nothing else. Includes fastembed + ONNX Runtime (~60 MB download on first run).
Ollama | `uv tool install code-context-engine` | Ollama running at localhost:11434 with `nomic-embed-text` pulled.

Using pipx instead of uv:

Terminal window

    pipx install "code-context-engine[local]"

Caution

Installing without `[local]` and without Ollama running will cause `cce init` to fail with “No embedding backend available.” Always pick one of the two options above.

## Initialize your project

Section titled “Initialize your project”
Terminal window

    cd /path/to/your/projectcce init

This does everything:

- Detects your embedding backend (fastembed or Ollama)
- Builds vector, FTS, and graph indexes
- Installs git hooks (auto-updates index on commit)
- Writes MCP config for detected editors
- Creates instruction files with output compression rules

### Target a specific agent

Section titled “Target a specific agent”
Terminal window

    cce init --agent claude     # Claude Code onlycce init --agent codex      # Codex CLI onlycce init --agent copilot    # VS Code / Copilot onlycce init --agent all        # Every supported editor

## Verify it works

Section titled “Verify it works”

Restart your editor, then ask a question about your code. The agent will call `context_search` via MCP instead of reading files.

Check your savings:

Terminal window

    cce savings

      my-project · 5 queries
      ⛁ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶ ⛶  93% tokens saved
      Input savings   42.1k  tokens   $0.63  Output savings  1.2k  tokens   $0.09  ──────────────────────────────────────────  Total saved   43.3k  tokens   $0.72

## Embedding backends

Section titled “Embedding backends”

CCE auto-detects the best available backend at init time:

1. fastembed (with `[local]` extra) — Uses `BAAI/bge-small-en-v1.5`. Works offline, no external services needed. ~60 MB model downloaded on first run.
2. Ollama — If running at localhost:11434 with `nomic-embed-text` pulled. Zero extra Python dependencies.

Force a specific backend with `CCE_EMBED_BACKEND=fastembed` or `CCE_EMBED_BACKEND=ollama`.

## Next steps

Section titled “Next steps”

- Multi-agent setup — Configure all your editors
- Configuration — Tune compression, embedding, and more
- CLI Reference — All available commands