curl --request POST \
--url https://control-plane.kubiya.ai/api/v1/agents \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"name": "<string>",
"description": "<string>",
"system_prompt": "<string>",
"capabilities": [
"<unknown>"
],
"configuration": {},
"model_id": "<string>",
"model": "<string>",
"llm_config": {},
"runtime": "<string>",
"runner_name": "<string>",
"team_id": "<string>",
"environment_ids": [
"<string>"
],
"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/agents"
payload = {
"name": "<string>",
"description": "<string>",
"system_prompt": "<string>",
"capabilities": ["<unknown>"],
"configuration": {},
"model_id": "<string>",
"model": "<string>",
"llm_config": {},
"runtime": "<string>",
"runner_name": "<string>",
"team_id": "<string>",
"environment_ids": ["<string>"],
"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>',
system_prompt: '<string>',
capabilities: ['<unknown>'],
configuration: {},
model_id: '<string>',
model: '<string>',
llm_config: {},
runtime: '<string>',
runner_name: '<string>',
team_id: '<string>',
environment_ids: ['<string>'],
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/agents', 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/agents",
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>',
'system_prompt' => '<string>',
'capabilities' => [
'<unknown>'
],
'configuration' => [
],
'model_id' => '<string>',
'model' => '<string>',
'llm_config' => [
],
'runtime' => '<string>',
'runner_name' => '<string>',
'team_id' => '<string>',
'environment_ids' => [
'<string>'
],
'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/agents"
payload := strings.NewReader("{\n \"name\": \"<string>\",\n \"description\": \"<string>\",\n \"system_prompt\": \"<string>\",\n \"capabilities\": [\n \"<unknown>\"\n ],\n \"configuration\": {},\n \"model_id\": \"<string>\",\n \"model\": \"<string>\",\n \"llm_config\": {},\n \"runtime\": \"<string>\",\n \"runner_name\": \"<string>\",\n \"team_id\": \"<string>\",\n \"environment_ids\": [\n \"<string>\"\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/agents")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"name\": \"<string>\",\n \"description\": \"<string>\",\n \"system_prompt\": \"<string>\",\n \"capabilities\": [\n \"<unknown>\"\n ],\n \"configuration\": {},\n \"model_id\": \"<string>\",\n \"model\": \"<string>\",\n \"llm_config\": {},\n \"runtime\": \"<string>\",\n \"runner_name\": \"<string>\",\n \"team_id\": \"<string>\",\n \"environment_ids\": [\n \"<string>\"\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/agents")
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 \"system_prompt\": \"<string>\",\n \"capabilities\": [\n \"<unknown>\"\n ],\n \"configuration\": {},\n \"model_id\": \"<string>\",\n \"model\": \"<string>\",\n \"llm_config\": {},\n \"runtime\": \"<string>\",\n \"runner_name\": \"<string>\",\n \"team_id\": \"<string>\",\n \"environment_ids\": [\n \"<string>\"\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>",
"system_prompt": "<string>",
"status": "<string>",
"capabilities": [
"<unknown>"
],
"configuration": {},
"model_id": "<string>",
"llm_config": {},
"runtime": "<string>",
"runner_name": "<string>",
"team_id": "<string>",
"created_at": "<string>",
"updated_at": "<string>",
"last_active_at": "<string>",
"state": {},
"error_message": "<string>",
"projects": [
{}
],
"environments": [
{}
],
"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>"
}
]
}Create Agent
Create a new agent in the organization
curl --request POST \
--url https://control-plane.kubiya.ai/api/v1/agents \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"name": "<string>",
"description": "<string>",
"system_prompt": "<string>",
"capabilities": [
"<unknown>"
],
"configuration": {},
"model_id": "<string>",
"model": "<string>",
"llm_config": {},
"runtime": "<string>",
"runner_name": "<string>",
"team_id": "<string>",
"environment_ids": [
"<string>"
],
"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/agents"
payload = {
"name": "<string>",
"description": "<string>",
"system_prompt": "<string>",
"capabilities": ["<unknown>"],
"configuration": {},
"model_id": "<string>",
"model": "<string>",
"llm_config": {},
"runtime": "<string>",
"runner_name": "<string>",
"team_id": "<string>",
"environment_ids": ["<string>"],
"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>',
system_prompt: '<string>',
capabilities: ['<unknown>'],
configuration: {},
model_id: '<string>',
model: '<string>',
llm_config: {},
runtime: '<string>',
runner_name: '<string>',
team_id: '<string>',
environment_ids: ['<string>'],
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/agents', 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/agents",
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>',
'system_prompt' => '<string>',
'capabilities' => [
'<unknown>'
],
'configuration' => [
],
'model_id' => '<string>',
'model' => '<string>',
'llm_config' => [
],
'runtime' => '<string>',
'runner_name' => '<string>',
'team_id' => '<string>',
'environment_ids' => [
'<string>'
],
'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/agents"
payload := strings.NewReader("{\n \"name\": \"<string>\",\n \"description\": \"<string>\",\n \"system_prompt\": \"<string>\",\n \"capabilities\": [\n \"<unknown>\"\n ],\n \"configuration\": {},\n \"model_id\": \"<string>\",\n \"model\": \"<string>\",\n \"llm_config\": {},\n \"runtime\": \"<string>\",\n \"runner_name\": \"<string>\",\n \"team_id\": \"<string>\",\n \"environment_ids\": [\n \"<string>\"\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/agents")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"name\": \"<string>\",\n \"description\": \"<string>\",\n \"system_prompt\": \"<string>\",\n \"capabilities\": [\n \"<unknown>\"\n ],\n \"configuration\": {},\n \"model_id\": \"<string>\",\n \"model\": \"<string>\",\n \"llm_config\": {},\n \"runtime\": \"<string>\",\n \"runner_name\": \"<string>\",\n \"team_id\": \"<string>\",\n \"environment_ids\": [\n \"<string>\"\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/agents")
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 \"system_prompt\": \"<string>\",\n \"capabilities\": [\n \"<unknown>\"\n ],\n \"configuration\": {},\n \"model_id\": \"<string>\",\n \"model\": \"<string>\",\n \"llm_config\": {},\n \"runtime\": \"<string>\",\n \"runner_name\": \"<string>\",\n \"team_id\": \"<string>\",\n \"environment_ids\": [\n \"<string>\"\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>",
"system_prompt": "<string>",
"status": "<string>",
"capabilities": [
"<unknown>"
],
"configuration": {},
"model_id": "<string>",
"llm_config": {},
"runtime": "<string>",
"runner_name": "<string>",
"team_id": "<string>",
"created_at": "<string>",
"updated_at": "<string>",
"last_active_at": "<string>",
"state": {},
"error_message": "<string>",
"projects": [
{}
],
"environments": [
{}
],
"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
Enter your Kubiya API token (format: Bearer )
Body
Agent name
Agent description
System prompt for the agent
Agent capabilities
Agent configuration
LiteLLM model identifier
Model identifier (alias for model_id)
Model-specific configuration
Runtime type: 'default' (Agno) or 'claude_code' (Claude Code SDK)
Preferred runner for this agent
Team ID to assign this agent to
Environment IDs to deploy this agent to
Tool set IDs to associate with this agent
Tool set configurations keyed by skill ID
Show child attributes
Show child attributes
Execution environment: env vars, secrets, integrations
Show child attributes
Show child attributes
Response
Successful Response
Projects this agent belongs to
Environments this agent is deployed to
IDs of associated skills
Associated skills with details
Execution environment configuration for agents/teams
Show child attributes
Show child attributes
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