> ## Documentation Index
> Fetch the complete documentation index at: https://docs.observal.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Use Cases

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](https://docs.observal.io/use-cases/observe-mcp-traffic.md) |
| Package an agent once and ship it to any harness | [Share agent configs across harnesses](https://docs.observal.io/use-cases/share-agent-configs.md) |
| Figure out why a session went wrong | [Debug agent failures](https://docs.observal.io/use-cases/debug-agent-failures.md) |
| Give your whole team a source of truth | [Run a team-wide agent registry](https://docs.observal.io/use-cases/team-registry.md) |
| Adapt an approved agent or component without changing the original | [Fork and customize](https://docs.observal.io/use-cases/fork-and-customize.md) |

## How these relate

```mermaid theme={null}
flowchart LR
    observe[Observe MCP traffic]
    debug[Debug agent failures]
    share[Share agent configs]
    registry[Team registry]

    observe -->|traces give you evidence| debug
    observe --> share
    share -->|governance + reuse| registry
```

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.


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.