> For the complete documentation index, see [llms.txt](https://docs.ox.security/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ox.security/vibesec/agent-ai-bom.md).

# AI Inventory: Agent AI BOM

The Agent AI BOM page provides an inventory of the AI ecosystem surrounding your organization's AI coding agents.

It gives security teams visibility into the components and services used by AI coding agents, such as MCP servers, external SaaS systems, and AI models, helping them understand and govern the organization's AI stack.

OX correlates those events into the entries shown on this page, so you can answer questions such as:

* Which MCP servers is your team using
* Which external SaaS systems are agents reaching into
* Which AI models are the agents running on
* Which developers are calling them
* How often each one is used
* When each was last active

<figure><img src="/files/BdbOgo4EU8LSzplMTHvG" alt="" width="563"><figcaption></figcaption></figure>

From the Agent AI BOM page, you can open the following tabs:

* [**MCP Servers**:](/vibesec/agent-ai-bom/agent-ai-bom-mcp-servers.md) The MCP servers your developers have wired up to their AI coding agents.
* [**External SaaS**:](/vibesec/agent-ai-bom/agent-ai-bom-external-saas.md) Third-party SaaS systems (such as GitHub, GitLab, Jira, Slack, AWS, and Kubernetes) that agents reach into through commands.
* [**AI Models**:](/vibesec/agent-ai-bom/agent-ai-bom-ai-models.md) The AI models powering agent reasoning and code generation.


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# 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.ox.security/vibesec/agent-ai-bom.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.