> For the complete documentation index, see [llms.txt](https://docs.trustlogix.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.trustlogix.io/trust-ai/ai-agents/register-an-ai-agent.md).

# Register an AI Agent

## 1. Create Agent

* To register an AI Agent into the TrustLogix system, you can navigate to the **AI Agents** screen using the top left menu. 
* Here, you can click **Create Agent**, and provide name, description, and status.

{% hint style="info" %}
Only AI Agents set to the **"ACTIVE"** status will be available in the policy engine
{% endhint %}

## 2. Configure Agent

* Once created, you **MUST** set up the agent configuration. Navigate to the created AI Agent, then to the **Configuration** tab. 
* Here, you have the option to configure the **Entitlement Source** and **OAuth**.

{% hint style="warning" %}
Currently, only other registered data accounts are supported as entitlement sources. Direct entitlement sync from configurable sources is a planned feature.
{% endhint %}

* OAuth configuration corresponds to the **AI Agent** identity. 
* We currently recommend using an existing registered application, as this identity will be used for agent activity monitoring in other registered systems in TrustLogix as well as **Just-In-Time** policies. 

{% hint style="warning" %}
Ensure the provided scope follows **Client-Credential/Self-Issued** scope formats according to your Identity Provider (i.e. Azure uses 'api://{client-id}/.default', Okta uses 'default', etc)
{% endhint %}

{% hint style="info" %}
If connecting to **Databricks**, select "**OAuth User to Machine Per User**" for Auth type. 
{% endhint %}

* After completing the form and clicking **Save**, an optional **API-Key** is generated, which can be used for additional security if securing a **custom** AI Agent by including it in the request headers of the MCP Client. 

## 3. Connecting Agent

* To communicate with AI Agents, TrustAI utilizes the **MCP** protocol to offer real-time policy decisions with respect to user identity, agent identity, and a host of conditions.
* See [MCP Server](/trust-ai/mcp-server.md) for more details. 

{% hint style="warning" %}
A common concern with connecting via MCP is the non-determinism in whether a policy is evaluated, as the AI Agent must call the tool. \
\
We recommend distributing responsibilities across your agents and orchestrating according to responses from the TrustAI MCP Server.\
\
If managing deployment yourself (i.e. LangSmith), LLM guardrails must be implemented by developers. 
{% endhint %}


---

# 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
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```
GET https://docs.trustlogix.io/trust-ai/ai-agents/register-an-ai-agent.md?ask=<question>&goal=<endgoal>
```

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