Klaudia Work Surfaces - Beyond The UI

Klaudia is not limited to the Komodor UI. It can be embedded directly into the organizational existing operational environment, where engineers already work and where incidents are already managed.

This allows teams to trigger investigations, consume RCA results, ask follow-up questions, and approve remediation actions from their own workflows — including Slack channels, CI/CD pipelines, incident response tools, internal platforms, AI agents, and MCP-compatible clients.

The goal is to make Klaudia available at the point of action: inside the tools engineers already use during deployments, alerts, incidents, and troubleshooting — without requiring them to switch context into Komodor every time.

Slack

A Klaudia bot natively embedded in Slack lets engineers run full investigations without leaving their operational channels:

• Trigger RCA investigations from a Slack message or war room
• Ask follow-up questions and get answers in-thread
• Review and approve remediation actions directly in Slack
• Receive investigation summaries and root cause verdicts as messages

Getting Started

Get started here with Klaudia for Slack.

REST API

Klaudia’s Root Cause Analysis (RCA) is now available through the Komodor API—enabling teams to trigger and retrieve AI-powered investigations directly from their existing toolchains and workflows.

Available Endpoints

• Trigger RCA — POST /api/v1/klaudia/rca
  Initiates an RCA for a specific Kubernetes workload (Pod, Deployment, Job).
• Retrieve Results — GET /api/v1/klaudia/rca/{session_id}
  Returns the root cause, confidence score, supporting evidence, and suggested remediation steps.

Usage Pattern

Investigations typically complete in 20–30 seconds. Use a polling pattern:

1. Trigger investigation via POST /api/v1/klaudia/rca
2. Receive a session_id in the response
3. Poll GET /api/v1/klaudia/rca/{session_id} until complete
4. Process the returned root cause analysis and recommendations

Common use cases:

• Automate post-deployment troubleshooting by integrating directly into CI/CD tools like Jenkins, GitLab, or CircleCI. 
  • Example CI/CD script
• Enhance incident response workflows in alerting platforms like PagerDuty and OpsGenie
• Bring RCA insights into ChatOps tools such as Slack or Microsoft Teams
• Centralize visibility by embedding RCA outputs into dashboards and internal ticketing systems

Getting Started

Explore the new endpoints in our public Swagger documentation. The RCA API uses the same Komodor authentication and permission model you’re already familiar with.

MCP Server (Beta)

Expose Klaudia as a standardized tool that external platforms and AI agents can discover and invoke — without custom API integrations. IDEs, CI/CD pipelines, autonomous agents, and internal tools can trigger investigations through a common protocol, embedding Klaudia across your ecosystem.

Supported clients: Claude, VS Code, Cursor, LLM agents, and any MCP-compatible platform.

• The server runs locally on your machine. It is distributed as a Python package on PyPI and launched via uvx or uv run.
• Two transport modes are supported:
  • HTTP: the server starts on http://localhost:8002 and the AI client connects to it over HTTP.
  • stdio (development): the AI client spawns the server as a subprocess and communicates via stdin/stdout. Supported by most MCP-compatible clients.
• It talks to Komodor's API over HTTPS using your API key.
• It is read-only. The tools expose observability and analysis capabilities only. 
  One Click Remediation is not currently exposed.

Getting Started

For installation instructions, prerequisites, and AI client configuration, see the official package page: komodor-mcp on PyPI →