Overview

Observal solves five concrete problems in the AI-agent lifecycle. Each page below is written as a playbook: what the problem is, how Observal addresses it, and the exact commands to run.

If you need to...	Read
See what your MCP servers are actually doing	Observe MCP traffic
Package an agent once and ship it to any harness	Share agent configs across harnesses
Figure out why a session went wrong	Debug agent failures
Give your whole team a source of truth	Run a team-wide agent registry

How these relate

You typically adopt Observal in that order: observe first (low-risk, instant value), then debug, then share, and finally run a team registry once you have enough published agents to justify governance.