import { Callout, Steps, Tabs, Cards } from "@/docs/components";

AI Agents

AI Agents are the core of elizaOS Cloud. Each agent is a conversational AI with its own personality, knowledge, and capabilities.

<div className="status-badge status-stable">Stable</div>

Overview

An agent in elizaOS Cloud consists of:

Character Configuration: Personality, bio, and style settings
Model Settings: AI model provider and parameters
Knowledge Base: Documents and data for RAG
MCP Connections: External tools and integrations
Deployment Settings: Runtime configuration

Creating an Agent

Using the Dashboard

<Steps> ### Navigate to My Agents Go to [Dashboard → My Agents](/dashboard/my-agents) and click "Create Agent".

Configure Character

Fill in the agent's personality:

Name: Display name for your agent
Bio: Background and expertise
Style: Communication tone and formatting

Select Model

Choose from the model providers and models currently available in the model catalog.

Deploy

Click "Deploy" to launch your agent.

</Steps> </Tabs.Tab> <Tabs.Tab> ### Using the API

bash

curl -X POST "https://elizacloud.ai/api/v1/app/agents" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Research Assistant",
    "bio": "Expert in scientific research and data analysis"
  }'

Response:

json

{
  "success": true,
  "agent": {
    "id": "uuid-abc123",
    "name": "Research Assistant",
    "username": "research-assistant",
    "bio": ["Expert in scientific research and data analysis"],
    "created_at": "2024-01-15T10:30:00Z"
  }
}

</Tabs.Tab> <Tabs.Tab>

Using the CLI

bash

# Install the scaffolding CLI
bun add -g elizaos

# Create a local project
elizaos create research-assistant --template project
cd research-assistant

# Run the generated project scripts
bun install
bun run dev

</Tabs.Tab> </Tabs>

Character Configuration

The character JSON defines your agent's personality and behavior.

json

{
  "name": "Research Assistant",
  "bio": [
    "Expert researcher with deep knowledge in scientific literature",
    "Specializes in data analysis and synthesis",
    "Values accuracy and proper citation"
  ],
  "lore": [
    "Trained on millions of academic papers",
    "Developed by a team of PhD researchers"
  ],
  "style": {
    "all": [
      "Professional and academic tone",
      "Evidence-based reasoning",
      "Clear and structured responses"
    ],
    "chat": ["Concise yet thorough", "Ask clarifying questions when needed"],
    "post": ["Formal academic style", "Include citations"]
  },
  "topics": ["science", "research", "data analysis", "academic writing"],
  "adjectives": ["knowledgeable", "thorough", "precise", "helpful"],
  "modelProvider": "openai",
  "settings": {
    "model": "gpt-4o",
    "temperature": 0.7,
    "maxTokens": 4096
  }
}

Character Fields

Field	Type	Description
`name`	string	Display name of the agent
`bio`	string[]	Array of background/expertise statements
`lore`	string[]	Additional context and backstory
`style.all`	string[]	Global style instructions
`style.chat`	string[]	Chat-specific instructions
`style.post`	string[]	Social media post instructions
`topics`	string[]	Areas of expertise
`adjectives`	string[]	Personality descriptors
`modelProvider`	string	AI provider (openai, anthropic, google)
`settings`	object	Model-specific settings

Agent Management

List Agents

bash

curl -X GET "https://elizacloud.ai/api/my-agents/characters" \
  -H "Authorization: Bearer YOUR_API_KEY"

Get Agent Details

bash

curl -X GET "https://elizacloud.ai/api/my-agents/characters/{agentId}" \
  -H "Authorization: Bearer YOUR_API_KEY"

Delete Agent

bash

curl -X DELETE "https://elizacloud.ai/api/my-agents/characters/{agentId}" \
  -H "Authorization: Bearer YOUR_API_KEY"

Agent Status

Agents can be in one of these states:

Status	Description
`active`	Agent is running and accepting requests
`paused`	Agent is temporarily disabled
`deploying`	Agent deployment in progress
`error`	Agent encountered an error

Monetization

Publish your agents to the marketplace and earn from usage.

bash

curl -X POST "https://elizacloud.ai/api/v1/agents/{agentId}/publish" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "pricing": {
      "perMessage": 0.001,
      "perMinute": 0.01
    },
    "visibility": "public"
  }'

<Callout type="info"> Learn more about agent monetization in the [Earnings](/docs/earnings) documentation. </Callout>

Best Practices

Clear Instructions — Provide specific style guidelines for consistent behavior
Test Thoroughly — Use the API Explorer to test your agent before publishing
Monitor Usage — Track agent analytics in Dashboard to optimize performance
Iterate — Refine your agent based on user feedback

Next Steps

<Cards> <Cards.Card title="Agent Creator" href="/docs/agent-creator"> Build agents with the visual editor </Cards.Card> <Cards.Card title="Character JSON" href="/docs/character-json"> Complete character configuration reference </Cards.Card> <Cards.Card title="Knowledge Base" href="/docs/documents"> Add documents for RAG capabilities </Cards.Card> <Cards.Card title="MCP Integration" href="/docs/mcps"> Connect external tools and services </Cards.Card> </Cards>