Connect an AI agent

Connect your preferred AI agent to Lira to create scenarios, manage assignments, and explore submitted results. The connection uses MCP, a standard that lets an agent work with Lira's tools on your behalf.

You need an Admin role in the Lira workspace. Each person signs in with their own account, and Lira checks their current access on every request.

Get your connection details

Open Settings → Integrations → AI agents in Lira. Choose your client, then use Copy setup for its connection steps. The server address for this Lira site is:

https://lira.thoughtly.com/mcp

If you use more than one Lira environment, copy the address from the workspace you intend to manage. You do not need to create or paste an API key.

Connect your agent

Choose the app you use. Keep Lira open while you complete the sign-in in your browser.

CodexClaudeChatGPTOther

Run these commands in your terminal, then sign in with your Lira admin account.

Copy Text

codex mcp add lira --url 'https://lira.thoughtly.com/mcp'
codex mcp login lira

1. In Codex, ask Lira to show your workspace and available tools.

If Lira is already configured, skip the add command and run codex mcp login lira. You can also manage the connection in Codex's MCP settings.

Codex MCP documentation

Add Lira's instructions

In AI agents, select Copy instructions and add them to the instructions your client uses for Lira. If the client supports installable skills, choose Download skill instead and follow that client's installation process. You can also read the current Lira instructions.

The instructions help your agent check the workspace, find real scenario and person IDs, preserve unrelated fields, and retry changes safely. They do not replace your client's permission or approval controls.

Try your first request

Start by confirming context:

Show my Lira workspace and the training tools I can use.

Then give the agent a specific task, such as:

• “Create an unpublished discovery scenario for our onboarding product. Show me the draft before publishing.”
• “Summarize training participation and submitted results for the last 30 days.”
• “Find the people assigned to this scenario and show their completion status.”

Review the workspace and proposed changes before approving a write. Ask the agent to report the outcome and link to the affected item in Lira. A queued generation or ingestion job is still in progress until it finishes.

What the connection can access

Agents can work with scenarios, shared training knowledge, assignments, permitted submitted results, coaching, reports, and certificates. Existing workspace privacy rules still apply. Private practice and private preparation are not exposed through an admin connection.

Recordings stay protected. Requesting a recording does not create a public sharing link. The connection does not manage member roles or invitations, change workspace privacy, place calls, or issue scores and certificates manually.

Manage or disconnect an agent

Return to Settings → Integrations → AI agents to see connection status and last successful use. Copying setup instructions does not create a connection. If Lira is waiting for the first request, return to your agent and ask it to show your workspace, then refresh the connection list.

Choose Disconnect to stop further requests immediately. Removing a server from your client and disconnecting it in Lira are separate actions. To use a disconnected connection again, choose Reconnect in Lira and sign in again if the client asks.

Troubleshooting

For training setup, see create a scenario. For shared results, see review submitted results.