Metadata-Version: 2.4
Name: nteract
Version: 2.2.1a202604180915
Summary: Bring AI to Jupyter notebooks. MCP server for Claude, ChatGPT, Gemini, OpenCode and any agent.
Author-email: Kyle Kelley <rgbkrk@gmail.com>
License-Expression: BSD-3-Clause
Requires-Python: >=3.10
Description-Content-Type: text/markdown

# nteract

A convenience wrapper that finds and launches `runt mcp` — the MCP server shipped with the [nteract desktop app](https://nteract.io).

**[Download the nteract desktop app](https://nteract.io)** — you'll need it to see notebooks, collaborate with agents, and manage environments.

> The recommended way to add the MCP server is `runt mcp` directly. This PyPI package is a convenience for users who prefer `uvx`.

### Quick Start

The MCP server ships with the desktop app. After installing, use `runt mcp` directly:

#### Claude Code

```bash
# Stable
claude mcp add nteract -- runt mcp

# Nightly
claude mcp add nteract-nightly -- runt-nightly mcp
```

#### Manual JSON config

```json
{
  "mcpServers": {
    "nteract": {
      "command": "runt",
      "args": ["mcp"]
    }
  }
}
```

#### Via this PyPI package

If `runt` isn't on your PATH, this package finds it in the app bundle:

```bash
claude mcp add nteract -- uvx nteract
```

That's it. Now Claude can execute Python code, create visualizations, and work with your data.

## What is this?

nteract is an MCP (Model Context Protocol) server that connects AI assistants like Claude to Jupyter notebooks. It enables:

- **Code execution**: Run Python in a persistent kernel
- **Real-time collaboration**: Watch the AI work in the nteract desktop app
- **Shared state**: Multiple agents can work on the same notebook
- **Environment management**: Automatic Python environment setup

## Example

Ask Claude:

> "Help me visualize my log data"

Claude will:
1. Connect to a notebook session
2. Write and execute code
3. Generate visualizations
4. Show you the results

You can open the same notebook in the [nteract desktop app](https://nteract.io) to see changes in real-time and collaborate with the AI.

## Available Tools

| Tool | Description |
|------|-------------|
| `list_active_notebooks` | List all open notebook sessions |
| `join_notebook` | Join an existing notebook session by ID |
| `open_notebook` | Open an existing .ipynb file |
| `create_notebook` | Create a new notebook |
| `save_notebook` | Save notebook to disk as .ipynb file |
| `create_cell` | Add a cell to the notebook (use `and_run=True` to execute) |
| `execute_cell` | Run a specific cell (returns partial results after timeout) |
| `run_all_cells` | Queue all code cells for execution |
| `set_cell` | Update a cell's source and/or type |
| `get_cell` | Get a cell by ID with outputs |
| `get_all_cells` | View all cells in the notebook |
| `replace_match` | Targeted literal text find-and-replace in a cell |
| `replace_regex` | Regex-based find-and-replace in a cell |
| `move_cell` | Reorder a cell within the notebook |
| `clear_outputs` | Clear a cell's outputs |
| `delete_cell` | Remove a cell from the notebook |
| `set_cells_source_hidden` | Show/hide cell source |
| `set_cells_outputs_hidden` | Show/hide cell outputs |
| `add_cell_tags` | Add tags to cells |
| `remove_cell_tags` | Remove tags from cells |
| `interrupt_kernel` | Interrupt the currently executing cell |
| `restart_kernel` | Restart kernel with updated dependencies |
| `show_notebook` | Open the notebook in the nteract desktop app (disabled with `--no-show`) |
| `add_dependency` | Add a Python package dependency |
| `remove_dependency` | Remove a dependency |
| `get_dependencies` | List current dependencies |
| `sync_environment` | Hot-install new deps without restart |

### CLI Flags

| Flag | Description |
|------|-------------|
| `--version` | Print version and exit |
| `--nightly` | Use `runt-nightly` (nightly daemon and app) |
| `--stable` | Use `runt` (stable daemon and app, default) |
| `--legacy` | Use the built-in Python MCP server instead of `runt mcp` |

By default, `nteract` finds and exec's the installed `runt` (or `runt-nightly`) binary. The `--legacy` flag falls back to the built-in Python MCP server.

## Architecture

```
┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│   Claude    │────▶│   nteract   │────▶│   runtimed  │
│  (or other  │     │ MCP Server  │     │   daemon    │
│     AI)     │     │             │     │             │
└─────────────┘     └─────────────┘     └──────┬──────┘
                                               │
                    ┌─────────────┐             │
                    │   nteract   │◀────────────┘
                    │ Desktop App │  (real-time sync)
                    └─────────────┘
```

- **nteract** (this package): MCP server for AI assistants
- **runtimed**: Low-level daemon and Python bindings ([docs](https://github.com/nteract/desktop))
- **nteract desktop**: Native app for humans to collaborate with AI

## Real-time Collaboration

The magic of nteract is that AI and humans share the same notebook:

1. AI connects via MCP and runs code
2. Human opens the same notebook in nteract desktop
3. Changes sync instantly via CRDT
4. Both see the same kernel state

This enables workflows like:
- AI does initial analysis, human refines
- Human writes code, AI debugs errors
- Multiple AI agents collaborate on complex tasks

## Development

```bash
# Clone
git clone https://github.com/nteract/desktop
cd desktop/python/nteract

# Install dependencies
uv sync

# Run tests
uv run pytest
```

## Related Projects

- [nteract/desktop](https://github.com/nteract/desktop) - Native desktop app
- [runtimed on PyPI](https://pypi.org/project/runtimed/) - Low-level Python bindings

## License

BSD-3-Clause
