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KDBL Context Lake

KDBL Context Lake (K-Lake) is a Kubernetes-native indexer that catalogs the files in your object stores and filesystems — so they can be searched, audited, and reasoned about as a single inventory, with grounded, verifiable AI answers on top.

Get started Connect your AI

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  • Introduction

    What K-Lake does, the core concepts (tenants, sources, crawls, tokens), and what you'll see running.

    Read the introduction

  • Quick start

    Sign in, add a source, extract and search its content, and open the original file behind any result.

    Quick start

  • Sources

    Configure S3, SMB/CIFS, SMBFS, and NFS sources — credentials, metadata caps, and lifecycle.

    Sources

  • AI over MCP

    Serve your content to Claude and other assistants over the Model Context Protocol — grounded answers, cited sources, per-user security.

    MCP server

Three interchangeable interfaces

Every action is scoped to your tenant and audited. Pick whichever suits you — they act on the same data.

The operator console: dashboards, source management, content search, tokens.

Web console guide

kdbl-control — seed crawls, manage sources, onboard tenants, check status.

CLI reference

Programmatic access to every operation.

REST API

Versioned docs

Use the version selector in the header to read the docs for the K-Lake release you're running. latest always points at the most recent stable release.

Authoring note — embedding media

These docs support images, animated GIFs, and video. For a YouTube embed, wrap an iframe in a video-embed div for a responsive 16:9 frame:

<div class="video-embed">
  <iframe src="https://www.youtube-nocookie.com/embed/VIDEO_ID"
          title="K-Lake demo" allowfullscreen></iframe>
</div>