curl --request POST \
  --url http://localhost:3000/v2/agents \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "<string>",
  "slug": "<string>",
  "description": "<string>",
  "icon": {},
  "status": "available",
  "format": "markdown",
  "source_file_id": "file_abc123",
  "model": "<string>",
  "instructions": "<string>",
  "execution_mode": "one_shot",
  "steps": [
    {
      "order": 2,
      "evaluations": [],
      "id": "<string>",
      "content": {},
      "outputExample": "<string>",
      "agentFileId": "<string>",
      "previewFileId": "<string>",
      "version": "<string>",
      "title": "<string>",
      "instructions": "<string>",
      "promptId": "<string>"
    }
  ],
  "evaluations": [
    {
      "type": "outcome",
      "rubric": "<string>",
      "maxIterations": 10.5
    }
  ],
  "skill_ids": [
    "<string>"
  ],
  "custom_tool_ids": [
    "<string>"
  ],
  "subagent_ids": [
    "<string>"
  ],
  "tool_configs": [
    {
      "enabled": true
    }
  ],
  "mcp_servers": [
    {
      "name": "<string>",
      "url": "<string>",
      "enabled": true,
      "tools": [
        {
          "name": "<string>",
          "enabled": true
        }
      ],
      "connection_account_id": "<string>"
    }
  ]
}
'

import requests

url = "http://localhost:3000/v2/agents"

payload = {
    "name": "<string>",
    "slug": "<string>",
    "description": "<string>",
    "icon": {},
    "status": "available",
    "format": "markdown",
    "source_file_id": "file_abc123",
    "model": "<string>",
    "instructions": "<string>",
    "execution_mode": "one_shot",
    "steps": [
        {
            "order": 2,
            "evaluations": [],
            "id": "<string>",
            "content": {},
            "outputExample": "<string>",
            "agentFileId": "<string>",
            "previewFileId": "<string>",
            "version": "<string>",
            "title": "<string>",
            "instructions": "<string>",
            "promptId": "<string>"
        }
    ],
    "evaluations": [
        {
            "type": "outcome",
            "rubric": "<string>",
            "maxIterations": 10.5
        }
    ],
    "skill_ids": ["<string>"],
    "custom_tool_ids": ["<string>"],
    "subagent_ids": ["<string>"],
    "tool_configs": [{ "enabled": True }],
    "mcp_servers": [
        {
            "name": "<string>",
            "url": "<string>",
            "enabled": True,
            "tools": [
                {
                    "name": "<string>",
                    "enabled": True
                }
            ],
            "connection_account_id": "<string>"
        }
    ]
}
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>',
    slug: '<string>',
    description: '<string>',
    icon: {},
    status: 'available',
    format: 'markdown',
    source_file_id: 'file_abc123',
    model: '<string>',
    instructions: '<string>',
    execution_mode: 'one_shot',
    steps: [
      {
        order: 2,
        evaluations: [],
        id: '<string>',
        content: {},
        outputExample: '<string>',
        agentFileId: '<string>',
        previewFileId: '<string>',
        version: '<string>',
        title: '<string>',
        instructions: '<string>',
        promptId: '<string>'
      }
    ],
    evaluations: [{type: 'outcome', rubric: '<string>', maxIterations: 10.5}],
    skill_ids: ['<string>'],
    custom_tool_ids: ['<string>'],
    subagent_ids: ['<string>'],
    tool_configs: [{enabled: true}],
    mcp_servers: [
      {
        name: '<string>',
        url: '<string>',
        enabled: true,
        tools: [{name: '<string>', enabled: true}],
        connection_account_id: '<string>'
      }
    ]
  })
};

fetch('http://localhost:3000/v2/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_PORT => "3000",
  CURLOPT_URL => "http://localhost:3000/v2/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>',
    'slug' => '<string>',
    'description' => '<string>',
    'icon' => [
        
    ],
    'status' => 'available',
    'format' => 'markdown',
    'source_file_id' => 'file_abc123',
    'model' => '<string>',
    'instructions' => '<string>',
    'execution_mode' => 'one_shot',
    'steps' => [
        [
                'order' => 2,
                'evaluations' => [
                                
                ],
                'id' => '<string>',
                'content' => [
                                
                ],
                'outputExample' => '<string>',
                'agentFileId' => '<string>',
                'previewFileId' => '<string>',
                'version' => '<string>',
                'title' => '<string>',
                'instructions' => '<string>',
                'promptId' => '<string>'
        ]
    ],
    'evaluations' => [
        [
                'type' => 'outcome',
                'rubric' => '<string>',
                'maxIterations' => 10.5
        ]
    ],
    'skill_ids' => [
        '<string>'
    ],
    'custom_tool_ids' => [
        '<string>'
    ],
    'subagent_ids' => [
        '<string>'
    ],
    'tool_configs' => [
        [
                'enabled' => true
        ]
    ],
    'mcp_servers' => [
        [
                'name' => '<string>',
                'url' => '<string>',
                'enabled' => true,
                'tools' => [
                                [
                                                                'name' => '<string>',
                                                                'enabled' => true
                                ]
                ],
                'connection_account_id' => '<string>'
        ]
    ]
  ]),
  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 := "http://localhost:3000/v2/agents"

	payload := strings.NewReader("{\n  \"name\": \"<string>\",\n  \"slug\": \"<string>\",\n  \"description\": \"<string>\",\n  \"icon\": {},\n  \"status\": \"available\",\n  \"format\": \"markdown\",\n  \"source_file_id\": \"file_abc123\",\n  \"model\": \"<string>\",\n  \"instructions\": \"<string>\",\n  \"execution_mode\": \"one_shot\",\n  \"steps\": [\n    {\n      \"order\": 2,\n      \"evaluations\": [],\n      \"id\": \"<string>\",\n      \"content\": {},\n      \"outputExample\": \"<string>\",\n      \"agentFileId\": \"<string>\",\n      \"previewFileId\": \"<string>\",\n      \"version\": \"<string>\",\n      \"title\": \"<string>\",\n      \"instructions\": \"<string>\",\n      \"promptId\": \"<string>\"\n    }\n  ],\n  \"evaluations\": [\n    {\n      \"type\": \"outcome\",\n      \"rubric\": \"<string>\",\n      \"maxIterations\": 10.5\n    }\n  ],\n  \"skill_ids\": [\n    \"<string>\"\n  ],\n  \"custom_tool_ids\": [\n    \"<string>\"\n  ],\n  \"subagent_ids\": [\n    \"<string>\"\n  ],\n  \"tool_configs\": [\n    {\n      \"enabled\": true\n    }\n  ],\n  \"mcp_servers\": [\n    {\n      \"name\": \"<string>\",\n      \"url\": \"<string>\",\n      \"enabled\": true,\n      \"tools\": [\n        {\n          \"name\": \"<string>\",\n          \"enabled\": true\n        }\n      ],\n      \"connection_account_id\": \"<string>\"\n    }\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("http://localhost:3000/v2/agents")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"name\": \"<string>\",\n  \"slug\": \"<string>\",\n  \"description\": \"<string>\",\n  \"icon\": {},\n  \"status\": \"available\",\n  \"format\": \"markdown\",\n  \"source_file_id\": \"file_abc123\",\n  \"model\": \"<string>\",\n  \"instructions\": \"<string>\",\n  \"execution_mode\": \"one_shot\",\n  \"steps\": [\n    {\n      \"order\": 2,\n      \"evaluations\": [],\n      \"id\": \"<string>\",\n      \"content\": {},\n      \"outputExample\": \"<string>\",\n      \"agentFileId\": \"<string>\",\n      \"previewFileId\": \"<string>\",\n      \"version\": \"<string>\",\n      \"title\": \"<string>\",\n      \"instructions\": \"<string>\",\n      \"promptId\": \"<string>\"\n    }\n  ],\n  \"evaluations\": [\n    {\n      \"type\": \"outcome\",\n      \"rubric\": \"<string>\",\n      \"maxIterations\": 10.5\n    }\n  ],\n  \"skill_ids\": [\n    \"<string>\"\n  ],\n  \"custom_tool_ids\": [\n    \"<string>\"\n  ],\n  \"subagent_ids\": [\n    \"<string>\"\n  ],\n  \"tool_configs\": [\n    {\n      \"enabled\": true\n    }\n  ],\n  \"mcp_servers\": [\n    {\n      \"name\": \"<string>\",\n      \"url\": \"<string>\",\n      \"enabled\": true,\n      \"tools\": [\n        {\n          \"name\": \"<string>\",\n          \"enabled\": true\n        }\n      ],\n      \"connection_account_id\": \"<string>\"\n    }\n  ]\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("http://localhost:3000/v2/agents")

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

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"name\": \"<string>\",\n  \"slug\": \"<string>\",\n  \"description\": \"<string>\",\n  \"icon\": {},\n  \"status\": \"available\",\n  \"format\": \"markdown\",\n  \"source_file_id\": \"file_abc123\",\n  \"model\": \"<string>\",\n  \"instructions\": \"<string>\",\n  \"execution_mode\": \"one_shot\",\n  \"steps\": [\n    {\n      \"order\": 2,\n      \"evaluations\": [],\n      \"id\": \"<string>\",\n      \"content\": {},\n      \"outputExample\": \"<string>\",\n      \"agentFileId\": \"<string>\",\n      \"previewFileId\": \"<string>\",\n      \"version\": \"<string>\",\n      \"title\": \"<string>\",\n      \"instructions\": \"<string>\",\n      \"promptId\": \"<string>\"\n    }\n  ],\n  \"evaluations\": [\n    {\n      \"type\": \"outcome\",\n      \"rubric\": \"<string>\",\n      \"maxIterations\": 10.5\n    }\n  ],\n  \"skill_ids\": [\n    \"<string>\"\n  ],\n  \"custom_tool_ids\": [\n    \"<string>\"\n  ],\n  \"subagent_ids\": [\n    \"<string>\"\n  ],\n  \"tool_configs\": [\n    {\n      \"enabled\": true\n    }\n  ],\n  \"mcp_servers\": [\n    {\n      \"name\": \"<string>\",\n      \"url\": \"<string>\",\n      \"enabled\": true,\n      \"tools\": [\n        {\n          \"name\": \"<string>\",\n          \"enabled\": true\n        }\n      ],\n      \"connection_account_id\": \"<string>\"\n    }\n  ]\n}"

response = http.request(request)
puts response.read_body

{
  "object": "page",
  "id": "p_abc123",
  "createdAt": "2024-01-15T10:30:00.000Z",
  "updatedAt": "2024-01-15T14:45:00.000Z",
  "name": "Project Management Agent",
  "slug": "project-management",
  "status": "available",
  "steps": [
    {
      "type": "audio",
      "order": 2,
      "evaluations": [],
      "id": "<string>",
      "content": {},
      "outputExample": "<string>",
      "structuredOutput": {
        "type": "json_schema",
        "name": "<string>",
        "schema": {},
        "description": "<string>",
        "strict": true
      },
      "agentFileId": "<string>",
      "previewFileId": "<string>",
      "version": "<string>",
      "title": "<string>",
      "instructions": "<string>",
      "promptId": "<string>"
    }
  ],
  "evaluations": [
    {
      "type": "outcome",
      "rubric": "<string>",
      "maxIterations": 10.5
    }
  ],
  "execution_mode": "one_shot",
  "orgId": "org_123",
  "sync_status": "pending",
  "web_access": {
    "enabled": true,
    "allowedHosts": [
      "<string>"
    ],
    "allowEveryUrl": true
  },
  "tool_configs": [
    {
      "name": "bash",
      "enabled": true,
      "permission_policy": "always_allow"
    }
  ],
  "mcp_servers": [
    {
      "name": "<string>",
      "url": "<string>",
      "enabled": true,
      "permission_policy": "always_allow",
      "tools": [
        {
          "name": "<string>",
          "enabled": true,
          "permission_policy": "always_allow"
        }
      ],
      "connection_account_id": "<string>"
    }
  ],
  "createdBy": {
    "object": "user",
    "id": "u_abc123",
    "apiKeyId": "bsk_abc123"
  },
  "updatedBy": {
    "object": "user",
    "id": "u_abc123",
    "apiKeyId": "bsk_abc123"
  },
  "description": "Manage projects with Kanban boards",
  "icon": {
    "type": "emoji",
    "emoji": "page_icon",
    "external": {
      "url": "https://example.com/image.jpg"
    },
    "file_upload": {
      "id": "fu_abc123"
    },
    "domain": "acme.com",
    "file": {
      "url": "https://s3.amazonaws.com/...",
      "expiryTime": "2024-01-15T10:30:00.000Z"
    },
    "lucide": "file-text",
    "brand": "github",
    "dicebear": {
      "style": "notionists-neutral",
      "seed": "0256de50-f90c-49a8-81f0-3988b2b89d8d",
      "backgroundColor": "b6e3f4,b6e3f4",
      "options": {
        "brows": "<string>",
        "eyes": "<string>",
        "glasses": "<string>",
        "lips": "<string>",
        "nose": "<string>",
        "flip": true,
        "rotate": 123,
        "scale": 123,
        "radius": 123,
        "size": 123,
        "backgroundType": "solid",
        "backgroundRotation": [
          123
        ],
        "translateX": 123,
        "translateY": 123,
        "clip": true,
        "randomizeIds": true
      }
    },
    "background": "blue",
    "empty": true,
    "updatedBy": "dataset:empresas"
  },
  "target_type": "company",
  "format": "markdown",
  "source_file_id": "<string>",
  "pptx_metadata": {
    "slideWidth": 123,
    "slideHeight": 123,
    "slideCount": 123,
    "title": "<string>",
    "author": "<string>"
  },
  "has_steps": false,
  "versions": [],
  "current_version": "<string>",
  "datasets": [
    "empresas",
    "pessoas"
  ],
  "sync_at": "<string>",
  "sync_error": "<string>",
  "skills_mode": "auto",
  "skill_ids": [
    "<string>"
  ],
  "instructions": "<string>",
  "tools_mode": "auto",
  "custom_tool_ids": [
    "<string>"
  ],
  "subagent_ids": [
    "<string>"
  ],
  "knowledge_file_ids": [
    "<string>"
  ]
}