Klaus Kode — the Agentic Data Integrator

What is Klaus Kode?

Klaus Kode is a Python-based Agentic Data Integrator that helps you vibe code your data integrations so you can connect to more systems, faster. You run it in your terminal as a workflow wizard.

• It uses AI agents (primarily Claude Code) to generate connector code, run and test that code, analyze logs, as well as manage dependencies and environment variables.
• It uses the Quix Cloud platform as a sandbox for running code in isolated containers and storing data.

Why use Klaus Kode?

To save time. A huge part of software and data engineering is simply about wrangling data. You need to get data out of one system and pipe it into another system, while preventing data loss. This usually requires writing custom “glue” code which is a lot of busywork. The data ecosystem is sprawling with pre-built connectors for a patchwork of different systems—some well-maintained, others barely touched. But instead of hunting down the right connector, why not get AI to help you build and test your own connectors?

Who is Klaus Kode for?

Klaus Kode is for engineers and other technical roles who need to build data pipelines but lack the required data engineering skills. The focus is on pipelines that require high throughput. If you’re dealing with a very small number of events (such as emails and chat messages from a handful of users), you might be better off with make.com or n8n.io.

Klaus Kode is best suited for scenarios where you need to integrate high-fidelity data sources — this could be continuous telemetry streams, blockchain transaction feeds, or large static datasets that need to be ingested and processed in a distributed manner.

Quick Start

Here are the major steps:

1. Install the Claude Code CLI: if you don't have it already

   • Windows users, you must install Claude using this command:
     irm https://claude.ai/install.ps1 | iex
     (This is due to limitations with claude.cmd—if you previously installed it using npm, please uninstall and reinstall using install.ps1.)

   • Linux/Mac users can run a similar command:
     curl -fsSL https://claude.ai/install.sh | bash

2. Clone this repo and navigate into the repo folder in a terminal window.

   git clone https://github.com/quixio/klaus-kode-agentic-integrator.git
   cd klaus-kode-agentic-integrator

3. Create a .env file: by copying the .env.example and adding your Quix PAT token and Anthropic API key.

   cp .env.example .env

4. Run the startup script: bash start.sh (Linux/Mac) or start.bat (Windows)

5. Follow the on-screen prompts.

For a more detailed explanation of what Klaus Kode is for and how to get started, see the following Getting Started guide:

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Getting Started with Klaus Kode

Prerequisites

You’ll need a few things already in place before you can start with Klaus Kode.

These include:

1. Python (3.12 or later) and Git installed on your system
2. The Claude Code CLI
3. A Quix project and PAT token
4. An Anthropic API token and billing enabled for the Anthropic APIs.
   * If you are a Quix customer and early beta tester, you might be able to get these keys from the Quix team

Klaus Kode has been tested on Ubuntu (via Windows WSL) and Mac OS. It should work on Windows too but has not been extensively tested on Windows.

Notes on Installing the Claude Code CLI

Klaus Kode leverages the Claude Code SDK under the hood, which in turn uses the Claude Code CLI. If you don't have an Anthropic account yet, sign up first.

According to Anthropic's official instructions, you install Claude Code like this:

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

However, if you are using Windows, you must install it using the install script. Existing npm-based installations will not work.

Here's how to run the install scripts for all operating systems:

(Linux/Mac)            curl -fsSL https://claude.ai/install.sh | bash

(Windows PowerShell)   irm https://claude.ai/install.ps1 | iex

Tokens and API Keys

Klaus Kode uses the Anthropic Sonnet API for log file analysis and Claude Code (also Sonnet) for code analysis and editing. Quix Cloud is used for deployments and sandbox testing.

In summary, you need the following keys and tokens:

1. An Anthropic API key — requires an Anthropic account with billing enabled and enough credit to run Claude Code.
2. A Quix Cloud PAT token — you can sign up for free to get one. (This lets Klaus Kode run the code in a cloud sandbox.)

Then configure your environment variables with these keys, as described in the following section.

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Klaus Kode Setup

To use Klaus Kode, clone the repo, add your environment variables, and run the startup script.

Here are those steps again in more detail:

1. Clone the Klaus Kode repo

git clone https://github.com/quixio/klaus-kode-agentic-integrator

2. Create a .env file (make a copy of the .env.example) and enter your API keys and PAT token:

ANTHROPIC_API_KEY=<your-anthropic-api-key> # "sk-ant-api..." - required for all AI operations
QUIX_TOKEN=<your-quix-token>                # "pat-..." 
QUIX_BASE_URL=https://portal-api.cloud.quix.io/

## OPTIONAL: If Klaus cannot automatically detect your Claude Code installation
CLAUDE_CLI_PATH=/home/username/.claude/local/node_modules/.bin

3. Run the startup script, which creates a virtual environment, activates it, and installs the dependencies from requirements.txt:

Linux/Mac

bash start.sh

Windows

./start.bat
OR
./start.ps1

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Klaus Kode Data Integration Workflow

You don't have to understand the workflow to get started—you can just give it a go and see what happens.

However, if you're used to using a free-form chat interface to generate code, it can be helpful to understand what awaits you.

Klaus Kode is different from most AI-based clients because it uses a cloud environment (Quix Cloud) to manage code rather than a local project. This cloud environment requires you to follow specific workflows.

When you start Klaus Kode, you’ll see the following options:

Select Workflow Type
--------------------
  ▶ 1. Source Workflow (Bring data in from another system)
    2. Sink Workflow (Write data out into an external system)
    3. Transform Workflow (Process data in flight) *Coming soon
    4. Debug Workflow (Diagnose and fix existing sandbox code) *Coming soon

Hopefully, the wording is straightforward enough to help you choose the right option.

Here's an overview of the steps in each workflow:

SOURCE WORKFLOW

SINK WORKFLOW

For more details, check out this End-to-end Tutorial. It shows you how to read from the Wikipedia "Change Event Stream" and sink the incoming page edit metadata into a Clickhouse Database (with a Kafka topic in the middle).