KumoRFM SDKEnvironment Setup

Claude Code

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Claude

Overview

This guide walks you through setting up the KumoSDK and Kumo Coding Agent with Anthropic Claude Code in desktop and CLI environments.

Claude Code is an AI coding agent by Anthropic. It can read your project files, write code, run commands, and iterate on errors. You interact with it by typing natural language prompts.

Prerequisites

Make sure you have:

  1. Python 3.10 to 3.13 installed
  2. Access to a KumoRFM environment, including an API key and any required API URL
  3. An Anthropic account
  4. Claude Code installed and authenticated. See the official Claude Code docs for desktop app and CLI installation.

Step 1: Create a Project

Create or open a project directory:

$mkdir my-kumo-project
$cd my-kumo-project

Desktop app: Open Claude Code and select your project folder.

CLI: Navigate to your project in the terminal.

Step 2: Install KumoSDK

$pip install kumoai

Verify:

$python -c "import kumoai; print(f'kumoai {kumoai.__version__} installed')"

Step 3: Authenticate with Kumo

Set your API key:

$export KUMO_API_KEY="YOUR_API_KEY_HERE"

Step 4: Install Kumo Coding Agent

The Kumo Coding Agent has two parts:

  • Context (knowledge base): Documentation, PQL rules, workflow guides, and data connector references that teach the agent how to use the Kumo platform. Installed by cloning the repository.
  • Skills (slash commands): Actions like /kumo-issue and /kumo-pr for reporting bugs and contributing fixes. Installed via npx skills add.

Install the context:

$git clone https://github.com/kumo-ai/kumo-coding-agent.git kumo-coding-agent
$echo 'Also read kumo-coding-agent/CLAUDE.md for Kumo agent capabilities.' >> CLAUDE.md

The second line tells Claude Code to read the agent’s knowledge base on startup.

Install the skills (optional):

$npx skills add kumo-ai/kumo-coding-agent --agent claude-code

Step 5: Use the Kumo Coding Agent

Desktop app:

  1. Open Claude Code
  2. Select your project folder (if not already open)
  3. Type a prompt in the chat panel:
Load the RelBench F1 dataset and predict whether each driver will finish in the top 3 in the next race
  1. Claude Code will read the Kumo Coding Agent context, inspect the data, build a graph, write PQL, and run the prediction.
  2. Review the changes Claude proposes. You can approve, edit, or reject each change before it is applied.

CLI:

Start an interactive session:

$cd my-kumo-project
$claude

This opens an interactive prompt. Type your request:

Load the RelBench F1 dataset and predict whether each driver will finish in the top 3 in the next race

You can also run a single prompt directly:

$claude "Load the RelBench F1 dataset and predict whether each driver will finish in the top 3 in the next race"

Step 6 (Optional): Upgrade

Upgrade KumoSDK:

$pip install --upgrade kumoai

Upgrade the Kumo Coding Agent:

$cd kumo-coding-agent && git pull

To pin to a specific version:

$cd kumo-coding-agent && git checkout v1.0.0

Troubleshooting

kumoai cannot be imported

$pip install kumoai

API key is missing

$export KUMO_API_KEY="YOUR_API_KEY_HERE"

Agent does not respond with Kumo knowledge

  • Verify kumo-coding-agent/ exists in your project directory
  • Verify your project’s CLAUDE.md contains the line referencing kumo-coding-agent/CLAUDE.md
  • Restart Claude Code or start a new session with claude

Claude Code CLI not found

$npm install -g @anthropic-ai/claude-code

Next Steps