Documentation Index
Fetch the complete documentation index at: https://docs.calseta.com/llms.txt
Use this file to discover all available pages before exploring further.
Calseta is under active development. APIs and features may change. We welcome feedback and contributions on GitHub.
Run Calseta locally
| Service | Port | Description |
|---|---|---|
| FastAPI server | 8000 | REST API for alerts, enrichment, workflows, and more |
| MCP server | 8001 | Model Context Protocol server for AI agents |
| UI | 5173 | Web dashboard for alert management and configuration |
| PostgreSQL | 5432 | Primary store and task queue |
Try the lab
The lab is a fully seeded demo environment with sample alerts, enrichment data, and a full-access API key. It’s the fastest way to explore Calseta’s capabilities:Create an API key
For non-lab usage, create your own API key:Open the UI
Once services are running, open http://localhost:5173 in your browser. The dashboard gives you a visual interface for managing alerts, configuring detection rules, enrichment providers, workflows, and more.
Next steps
How It Works
Understand the five-step pipeline: ingest, normalize, enrich, contextualize, and dispatch.
Authentication
Create API keys and authenticate your requests.
Alert Sources
Connect Microsoft Sentinel, Elastic, Splunk, or a generic webhook.
UI Dashboard
Explore the web dashboard for alert management and settings.
MCP Setup
Connect your AI agent to Calseta via the MCP server.

