agent-client-kernel

A Jupyter Kernel for the Agent Client Protocol (ACP)

This kernel allows you to interact with external ACP agents directly from Jupyter notebooks. It acts as an ACP client that connects to coding agents like Codex, providing a seamless notebook interface for AI-powered coding assistance.

About

This project implements a Jupyter kernel that serves as a client for coding agents via the Agent Client Protocol. The implementation uses MetaKernel as the base class, which provides built-in magics, shell commands, and other useful features.

The kernel spawns and communicates with external ACP agents (such as codex-acp) via stdio, allowing you to interact with AI coding assistants directly from your notebook.

Features

• ACP Client Implementation: Full client-side ACP protocol support
• External Agent Integration: Connects to any ACP-compatible agent
• Codex Support: Works with OpenAI Codex out of the box
• Based on MetaKernel: Built-in magics (help, shell, file operations, etc.)
• Configurable: Easily switch between different agents via environment variables
• Compatible with JupyterLab and Jupyter Notebook

Installation

Install the package:

pip install -e .

Install the kernel:

python -m agentclientkernel install --user

Configuration

The kernel connects to external ACP agents. By default, it uses codex-acp.

Using Codex (Default)

1. Install codex-acp:

   npm install -g @zed-industries/codex-acp
   # or download from https://github.com/zed-industries/codex-acp/releases

2. Set your OpenAI API key:

   export OPENAI_API_KEY=sk-...

3. Authorize Codex

   codex

   It will prompt you through authentication and permission to run stuff.

   This is the error you get when trying to chat with the agent then you probably missed this step.

Error: Authentication required

Make sure the ACP agent is configured correctly. Current agent: codex-acp

3. Start Jupyter and use the "Agent Client Protocol" kernel
   ```bash
   start-noteboook.py

Using Other Agents

Set environment variables to configure a different agent:

export ACP_AGENT_COMMAND=path/to/your/agent
export ACP_AGENT_ARGS="--arg1 --arg2"

Then start Jupyter normally. The kernel will use your configured agent.

Usage

After installation, create a new notebook and select "Agent Client Protocol" as the kernel.

Type your prompts in cells and execute them to interact with the agent:

Create a Python function to calculate fibonacci numbers

The agent will respond with code, explanations, and can help with:

• Writing code
• Debugging
• Code review
• Refactoring
• Documentation
• And more!

Magic Commands

The kernel provides a unified %agent magic command for all configuration and session management:

MCP Server Configuration:

• %agent mcp add NAME COMMAND [ARGS...] - Add an MCP server
• %agent mcp list - List configured MCP servers
• %agent mcp remove NAME - Remove an MCP server
• %agent mcp clear - Remove all MCP servers

Permission Configuration:

• %agent permissions [auto|manual|deny] - Set permission mode
• %agent permissions list - View permission request history

Session Management:

• %agent session new [CWD] - Create a new session
• %agent session info - Show current session information
• %agent session restart - Restart the current session

Agent Configuration:

• %agent config [COMMAND [ARGS...]] - Configure the agent command
• %agent env [KEY=VALUE] - Set agent environment variables

Use %agent without arguments to see all available subcommands. Use %agent? for detailed help on the magic command.

See the example notebooks in examples/ for demonstrations:

• basic_usage.ipynb - Basic agent interaction
• configuration_demo.ipynb - Configuration and session management

Requirements

• Python >= 3.10
• ipykernel >= 4.0
• jupyter-client >= 4.0
• agent-client-protocol >= 0.4.0
• metakernel >= 0.30.0
• An ACP-compatible agent (e.g., codex-acp)

Uninstallation

jupyter kernelspec remove agentclient
pip uninstall agentclientkernel

License

BSD 3-Clause License