---
title: Installation
description: Install Kitaru with uv or pip
---

Kitaru requires **Python 3.11 or newer**.

You can verify your interpreter with:

```bash
python --version
```

<Tabs items={["uv (recommended)", "pip"]}>
  <Tab value="uv (recommended)">
    ```bash
    uv add kitaru
    ```
  </Tab>
  <Tab value="pip">
    ```bash
    pip install kitaru
    ```
  </Tab>
</Tabs>

This gives you the full SDK, CLI, and everything you need to run flows locally.

## Optional extras

| Extra | What it adds |
|---|---|
| `local` | Local server and UI for browsing executions in a local web UI |
| `mcp` | MCP server for querying executions from AI assistants |
| `pydantic-ai` | PydanticAI adapter for wrapping agents in checkpoints |

```bash
uv add "kitaru[mcp,pydantic-ai,local]"
# or: pip install "kitaru[mcp,pydantic-ai,local]"
```

If you use Claude Code or another MCP-capable assistant, install
`kitaru[mcp]` so your assistant can query executions, inspect logs and
artifacts, provide input to waiting runs, and start replays through structured
tool calls. See [MCP Server](/agent-native/mcp-server) for setup.

## Verify Installation

<Tabs items={["uv project", "pip environment"]}>
  <Tab value="uv project">
    ```bash
    uv run kitaru --version
    uv run kitaru --help
    ```
  </Tab>
  <Tab value="pip environment">
    ```bash
    kitaru --version
    kitaru --help
    ```
  </Tab>
</Tabs>

## Local UI

If you installed the `local` extra, you can start a local server with a web
UI for browsing executions:

```bash
kitaru login
```

This launches the Kitaru server on your machine and opens the UI in your
browser. You can inspect flows, checkpoints, logs, and artifacts from any
execution you have run locally.

## Next Steps

Head to the [Quickstart](/getting-started/quickstart) to explore what's
available, see [Execution management](/guides/execution-management)
for lifecycle operations, or open [MCP Server](/agent-native/mcp-server)
for assistant-native querying.
