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POST
/
api
/
v1
/
teams
Create Team
curl --request POST \
  --url https://control-plane.kubiya.ai/api/v1/teams \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "<string>",
  "description": "<string>",
  "runtime": "default",
  "configuration": {
    "member_ids": [
      "<string>"
    ],
    "instructions": "",
    "reasoning": {
      "enabled": false,
      "model": "<string>",
      "agent_id": "<string>",
      "min_steps": 1,
      "max_steps": 10
    },
    "llm": {
      "model": "<string>",
      "temperature": 1,
      "max_tokens": 2,
      "top_p": 0.5,
      "top_k": 1,
      "stop": [
        "<string>"
      ],
      "frequency_penalty": 0,
      "presence_penalty": 0
    },
    "tools": [
      {}
    ],
    "knowledge_base": {},
    "session": {
      "user_id": "<string>",
      "session_id": "<string>",
      "auto_save": true,
      "persist": true
    },
    "dependencies": {},
    "markdown": true,
    "add_datetime_to_instructions": false,
    "structured_outputs": false,
    "response_model": "<string>",
    "debug_mode": false,
    "monitoring": false,
    "metadata": {}
  },
  "skill_ids": [
    "<string>"
  ],
  "skill_configurations": {},
  "execution_environment": {
    "working_dir": "<string>",
    "env_vars": {},
    "secrets": [
      "<string>"
    ],
    "integration_ids": [
      "<string>"
    ],
    "mcp_servers": {}
  }
}
'
import requests

url = "https://control-plane.kubiya.ai/api/v1/teams"

payload = {
    "name": "<string>",
    "description": "<string>",
    "runtime": "default",
    "configuration": {
        "member_ids": ["<string>"],
        "instructions": "",
        "reasoning": {
            "enabled": False,
            "model": "<string>",
            "agent_id": "<string>",
            "min_steps": 1,
            "max_steps": 10
        },
        "llm": {
            "model": "<string>",
            "temperature": 1,
            "max_tokens": 2,
            "top_p": 0.5,
            "top_k": 1,
            "stop": ["<string>"],
            "frequency_penalty": 0,
            "presence_penalty": 0
        },
        "tools": [{}],
        "knowledge_base": {},
        "session": {
            "user_id": "<string>",
            "session_id": "<string>",
            "auto_save": True,
            "persist": True
        },
        "dependencies": {},
        "markdown": True,
        "add_datetime_to_instructions": False,
        "structured_outputs": False,
        "response_model": "<string>",
        "debug_mode": False,
        "monitoring": False,
        "metadata": {}
    },
    "skill_ids": ["<string>"],
    "skill_configurations": {},
    "execution_environment": {
        "working_dir": "<string>",
        "env_vars": {},
        "secrets": ["<string>"],
        "integration_ids": ["<string>"],
        "mcp_servers": {}
    }
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)
const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({
    name: '<string>',
    description: '<string>',
    runtime: 'default',
    configuration: {
      member_ids: ['<string>'],
      instructions: '',
      reasoning: {
        enabled: false,
        model: '<string>',
        agent_id: '<string>',
        min_steps: 1,
        max_steps: 10
      },
      llm: {
        model: '<string>',
        temperature: 1,
        max_tokens: 2,
        top_p: 0.5,
        top_k: 1,
        stop: ['<string>'],
        frequency_penalty: 0,
        presence_penalty: 0
      },
      tools: [{}],
      knowledge_base: {},
      session: {user_id: '<string>', session_id: '<string>', auto_save: true, persist: true},
      dependencies: {},
      markdown: true,
      add_datetime_to_instructions: false,
      structured_outputs: false,
      response_model: '<string>',
      debug_mode: false,
      monitoring: false,
      metadata: {}
    },
    skill_ids: ['<string>'],
    skill_configurations: {},
    execution_environment: {
      working_dir: '<string>',
      env_vars: {},
      secrets: ['<string>'],
      integration_ids: ['<string>'],
      mcp_servers: {}
    }
  })
};

fetch('https://control-plane.kubiya.ai/api/v1/teams', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));
<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://control-plane.kubiya.ai/api/v1/teams",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'name' => '<string>',
    'description' => '<string>',
    'runtime' => 'default',
    'configuration' => [
        'member_ids' => [
                '<string>'
        ],
        'instructions' => '',
        'reasoning' => [
                'enabled' => false,
                'model' => '<string>',
                'agent_id' => '<string>',
                'min_steps' => 1,
                'max_steps' => 10
        ],
        'llm' => [
                'model' => '<string>',
                'temperature' => 1,
                'max_tokens' => 2,
                'top_p' => 0.5,
                'top_k' => 1,
                'stop' => [
                                '<string>'
                ],
                'frequency_penalty' => 0,
                'presence_penalty' => 0
        ],
        'tools' => [
                [
                                
                ]
        ],
        'knowledge_base' => [
                
        ],
        'session' => [
                'user_id' => '<string>',
                'session_id' => '<string>',
                'auto_save' => true,
                'persist' => true
        ],
        'dependencies' => [
                
        ],
        'markdown' => true,
        'add_datetime_to_instructions' => false,
        'structured_outputs' => false,
        'response_model' => '<string>',
        'debug_mode' => false,
        'monitoring' => false,
        'metadata' => [
                
        ]
    ],
    'skill_ids' => [
        '<string>'
    ],
    'skill_configurations' => [
        
    ],
    'execution_environment' => [
        'working_dir' => '<string>',
        'env_vars' => [
                
        ],
        'secrets' => [
                '<string>'
        ],
        'integration_ids' => [
                '<string>'
        ],
        'mcp_servers' => [
                
        ]
    ]
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}
package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://control-plane.kubiya.ai/api/v1/teams"

	payload := strings.NewReader("{\n  \"name\": \"<string>\",\n  \"description\": \"<string>\",\n  \"runtime\": \"default\",\n  \"configuration\": {\n    \"member_ids\": [\n      \"<string>\"\n    ],\n    \"instructions\": \"\",\n    \"reasoning\": {\n      \"enabled\": false,\n      \"model\": \"<string>\",\n      \"agent_id\": \"<string>\",\n      \"min_steps\": 1,\n      \"max_steps\": 10\n    },\n    \"llm\": {\n      \"model\": \"<string>\",\n      \"temperature\": 1,\n      \"max_tokens\": 2,\n      \"top_p\": 0.5,\n      \"top_k\": 1,\n      \"stop\": [\n        \"<string>\"\n      ],\n      \"frequency_penalty\": 0,\n      \"presence_penalty\": 0\n    },\n    \"tools\": [\n      {}\n    ],\n    \"knowledge_base\": {},\n    \"session\": {\n      \"user_id\": \"<string>\",\n      \"session_id\": \"<string>\",\n      \"auto_save\": true,\n      \"persist\": true\n    },\n    \"dependencies\": {},\n    \"markdown\": true,\n    \"add_datetime_to_instructions\": false,\n    \"structured_outputs\": false,\n    \"response_model\": \"<string>\",\n    \"debug_mode\": false,\n    \"monitoring\": false,\n    \"metadata\": {}\n  },\n  \"skill_ids\": [\n    \"<string>\"\n  ],\n  \"skill_configurations\": {},\n  \"execution_environment\": {\n    \"working_dir\": \"<string>\",\n    \"env_vars\": {},\n    \"secrets\": [\n      \"<string>\"\n    ],\n    \"integration_ids\": [\n      \"<string>\"\n    ],\n    \"mcp_servers\": {}\n  }\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}
HttpResponse<String> response = Unirest.post("https://control-plane.kubiya.ai/api/v1/teams")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"<string>\",\n  \"description\": \"<string>\",\n  \"runtime\": \"default\",\n  \"configuration\": {\n    \"member_ids\": [\n      \"<string>\"\n    ],\n    \"instructions\": \"\",\n    \"reasoning\": {\n      \"enabled\": false,\n      \"model\": \"<string>\",\n      \"agent_id\": \"<string>\",\n      \"min_steps\": 1,\n      \"max_steps\": 10\n    },\n    \"llm\": {\n      \"model\": \"<string>\",\n      \"temperature\": 1,\n      \"max_tokens\": 2,\n      \"top_p\": 0.5,\n      \"top_k\": 1,\n      \"stop\": [\n        \"<string>\"\n      ],\n      \"frequency_penalty\": 0,\n      \"presence_penalty\": 0\n    },\n    \"tools\": [\n      {}\n    ],\n    \"knowledge_base\": {},\n    \"session\": {\n      \"user_id\": \"<string>\",\n      \"session_id\": \"<string>\",\n      \"auto_save\": true,\n      \"persist\": true\n    },\n    \"dependencies\": {},\n    \"markdown\": true,\n    \"add_datetime_to_instructions\": false,\n    \"structured_outputs\": false,\n    \"response_model\": \"<string>\",\n    \"debug_mode\": false,\n    \"monitoring\": false,\n    \"metadata\": {}\n  },\n  \"skill_ids\": [\n    \"<string>\"\n  ],\n  \"skill_configurations\": {},\n  \"execution_environment\": {\n    \"working_dir\": \"<string>\",\n    \"env_vars\": {},\n    \"secrets\": [\n      \"<string>\"\n    ],\n    \"integration_ids\": [\n      \"<string>\"\n    ],\n    \"mcp_servers\": {}\n  }\n}")
  .asString();
require 'uri'
require 'net/http'

url = URI("https://control-plane.kubiya.ai/api/v1/teams")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"<string>\",\n  \"description\": \"<string>\",\n  \"runtime\": \"default\",\n  \"configuration\": {\n    \"member_ids\": [\n      \"<string>\"\n    ],\n    \"instructions\": \"\",\n    \"reasoning\": {\n      \"enabled\": false,\n      \"model\": \"<string>\",\n      \"agent_id\": \"<string>\",\n      \"min_steps\": 1,\n      \"max_steps\": 10\n    },\n    \"llm\": {\n      \"model\": \"<string>\",\n      \"temperature\": 1,\n      \"max_tokens\": 2,\n      \"top_p\": 0.5,\n      \"top_k\": 1,\n      \"stop\": [\n        \"<string>\"\n      ],\n      \"frequency_penalty\": 0,\n      \"presence_penalty\": 0\n    },\n    \"tools\": [\n      {}\n    ],\n    \"knowledge_base\": {},\n    \"session\": {\n      \"user_id\": \"<string>\",\n      \"session_id\": \"<string>\",\n      \"auto_save\": true,\n      \"persist\": true\n    },\n    \"dependencies\": {},\n    \"markdown\": true,\n    \"add_datetime_to_instructions\": false,\n    \"structured_outputs\": false,\n    \"response_model\": \"<string>\",\n    \"debug_mode\": false,\n    \"monitoring\": false,\n    \"metadata\": {}\n  },\n  \"skill_ids\": [\n    \"<string>\"\n  ],\n  \"skill_configurations\": {},\n  \"execution_environment\": {\n    \"working_dir\": \"<string>\",\n    \"env_vars\": {},\n    \"secrets\": [\n      \"<string>\"\n    ],\n    \"integration_ids\": [\n      \"<string>\"\n    ],\n    \"mcp_servers\": {}\n  }\n}"

response = http.request(request)
puts response.read_body
{
  "id": "<string>",
  "organization_id": "<string>",
  "name": "<string>",
  "description": "<string>",
  "configuration": {
    "member_ids": [
      "<string>"
    ],
    "instructions": "",
    "reasoning": {
      "enabled": false,
      "model": "<string>",
      "agent_id": "<string>",
      "min_steps": 1,
      "max_steps": 10
    },
    "llm": {
      "model": "<string>",
      "temperature": 1,
      "max_tokens": 2,
      "top_p": 0.5,
      "top_k": 1,
      "stop": [
        "<string>"
      ],
      "frequency_penalty": 0,
      "presence_penalty": 0
    },
    "tools": [
      {}
    ],
    "knowledge_base": {},
    "session": {
      "user_id": "<string>",
      "session_id": "<string>",
      "auto_save": true,
      "persist": true
    },
    "dependencies": {},
    "markdown": true,
    "add_datetime_to_instructions": false,
    "structured_outputs": false,
    "response_model": "<string>",
    "debug_mode": false,
    "monitoring": false,
    "metadata": {}
  },
  "created_at": "2023-11-07T05:31:56Z",
  "updated_at": "2023-11-07T05:31:56Z",
  "runtime": "default",
  "projects": [
    {}
  ],
  "skill_ids": [
    "<string>"
  ],
  "skills": [
    {}
  ],
  "execution_environment": {
    "working_dir": "<string>",
    "env_vars": {},
    "secrets": [
      "<string>"
    ],
    "integration_ids": [
      "<string>"
    ],
    "mcp_servers": {}
  }
}
{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}

Authorizations

​
Authorization
string
header
required

Enter your Kubiya API token (format: Bearer )

Body

application/json

Create a new team with full Agno capabilities

​
name
string
required

Team name

Required string length: 1 - 255
​
description
string | null

Team description

​
runtime
string | null
default:default

Runtime type for team leader: 'default' (Agno) or 'claude_code' (Claude Code SDK). Default: 'default'

​
configuration
TeamConfiguration · object

Team configuration aligned with Agno Team

​
skill_ids
string[]

Tool set IDs to associate with this team

​
skill_configurations
Skill Configurations · object

Tool set configurations keyed by skill ID

​
execution_environment
ExecutionEnvironment · object | null

Execution environment: env vars, secrets, integrations

Response

Successful Response

Team response with structured configuration

​
id
string
required
​
organization_id
string
required
​
name
string
required
​
description
string | null
required
​
status
enum<string>
required

Team status enumeration

Available options:
active,
inactive,
archived,
idle
​
configuration
TeamConfiguration · object
required

Comprehensive team configuration aligned with Agno's Team capabilities. This allows full control over team behavior, reasoning, tools, and LLM settings.

​
created_at
string<date-time>
required
​
updated_at
string<date-time>
required
​
runtime
string
default:default

Runtime type for team leader: 'default' (Agno) or 'claude_code' (Claude Code SDK)

​
projects
Projects · object[]

Projects this team belongs to

​
skill_ids
string[] | null

IDs of associated skills

​
skills
Skills · object[] | null

Associated skills with details

​
execution_environment
ExecutionEnvironment · object | null

Execution environment configuration for agents/teams