> ## Documentation Index
> Fetch the complete documentation index at: https://docs.crewai.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Kickoff Crew
> Kickoff a Crew on CrewAI AMP
## Overview
Once you've deployed your crew to the CrewAI AMP platform, you can kickoff executions through the web interface or the API. This guide covers both approaches.
## Method 1: Using the Web Interface
### Step 1: Navigate to Your Deployed Crew
1. Log in to [CrewAI AMP](https://app.crewai.com)
2. Click on the crew name from your projects list
3. You'll be taken to the crew's detail page
### Step 2: Initiate Execution
From your crew's detail page, you have two options to kickoff an execution:
#### Option A: Quick Kickoff
1. Click the `Kickoff` link in the Test Endpoints section
2. Enter the required input parameters for your crew in the JSON editor
3. Click the `Send Request` button
#### Option B: Using the Visual Interface
1. Click the `Run` tab in the crew detail page
2. Enter the required inputs in the form fields
3. Click the `Run Crew` button
### Step 3: Monitor Execution Progress
After initiating the execution:
1. You'll receive a response containing a `kickoff_id` - **copy this ID**
2. This ID is essential for tracking your execution
### Step 4: Check Execution Status
To monitor the progress of your execution:
1. Click the "Status" endpoint in the Test Endpoints section
2. Paste the `kickoff_id` into the designated field
3. Click the "Get Status" button
The status response will show:
* Current execution state (`running`, `completed`, etc.)
* Details about which tasks are in progress
* Any outputs produced so far
### Step 5: View Final Results
Once execution is complete:
1. The status will change to `completed`
2. You can view the full execution results and outputs
3. For a more detailed view, check the `Executions` tab in the crew detail page
## Method 2: Using the API
You can also kickoff crews programmatically using the CrewAI AMP REST API.
### Authentication
All API requests require a bearer token for authentication:
```bash theme={null}
curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
```
Your bearer token is available on the Status tab of your crew's detail page.
### Checking Crew Health
Before executing operations, you can verify that your crew is running properly:
```bash theme={null}
curl -H "Authorization: Bearer YOUR_CREW_TOKEN" https://your-crew-url.crewai.com
```
A successful response will return a message indicating the crew is operational:
```
Healthy%
```
### Step 1: Retrieve Required Inputs
First, determine what inputs your crew requires:
```bash theme={null}
curl -X GET \
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
https://your-crew-url.crewai.com/inputs
```
The response will be a JSON object containing an array of required input parameters, for example:
```json theme={null}
{ "inputs": ["topic", "current_year"] }
```
This example shows that this particular crew requires two inputs: `topic` and `current_year`.
### Step 2: Kickoff Execution
Initiate execution by providing the required inputs:
```bash theme={null}
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
-d '{"inputs": {"topic": "AI Agent Frameworks", "current_year": "2025"}}' \
https://your-crew-url.crewai.com/kickoff
```
The response will include a `kickoff_id` that you'll need for tracking:
```json theme={null}
{ "kickoff_id": "abcd1234-5678-90ef-ghij-klmnopqrstuv" }
```
### Step 3: Check Execution Status
Monitor the execution progress using the kickoff\_id:
```bash theme={null}
curl -X GET \
-H "Authorization: Bearer YOUR_CREW_TOKEN" \
https://your-crew-url.crewai.com/status/abcd1234-5678-90ef-ghij-klmnopqrstuv
```
## Handling Executions
### Long-Running Executions
For executions that may take a long time:
1. Consider implementing a polling mechanism to check status periodically
2. Use webhooks (if available) for notification when execution completes
3. Implement error handling for potential timeouts
### Execution Context
The execution context includes:
* Inputs provided at kickoff
* Environment variables configured during deployment
* Any state maintained between tasks
### Debugging Failed Executions
If an execution fails:
1. Check the "Executions" tab for detailed logs
2. Review the "Traces" tab for step-by-step execution details
3. Look for LLM responses and tool usage in the trace details
Contact our support team for assistance with execution issues or questions
about the Enterprise platform.