> For the complete documentation index, see [llms.txt](https://docs.observal.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.observal.io/use-cases/use-cases.md).

# 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](/use-cases/observe-mcp-traffic.md)                  |
| Package an agent once and ship it to any harness | [Share agent configs across harnesses](/use-cases/share-agent-configs.md) |
| Figure out why a session went wrong              | [Debug agent failures](/use-cases/debug-agent-failures.md)                |
| Give your whole team a source of truth           | [Run a team-wide agent registry](/use-cases/team-registry.md)             |

## How these relate

```mermaid
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.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.observal.io/use-cases/use-cases.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.