> ## Documentation Index
> Fetch the complete documentation index at: https://ekacare-fix-ts-sdk-github-npm-links.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Build your first AI agent with Echo in 5 minutes

Get started with [Echo](https://github.com/eka-care/echo-sdk) in 5 minutes.

<Steps>
  <Step title="Install">
    ```bash theme={null}
    pip install echo-sdk
    ```
  </Step>

  <Step title="Set API Key">
    ```bash theme={null}
    export OPENAI_API_KEY=sk-...
    # or ANTHROPIC_API_KEY or GOOGLE_API_KEY
    ```
  </Step>

  <Step title="Create Agent">
    ```python theme={null}
    import asyncio
    from echo import (
        GenericAgent, AgentConfig, LLMConfig,
        PersonaConfig, TaskConfig, ConversationContext,
        Message, MessageRole, TextMessage
    )

    # LLM configuration
    llm_config = LLMConfig(
        provider="openai",
        model="gpt-4o-mini",
        temperature=0.2,
        max_tokens=2000,
    )

    # Agent configuration (persona + task = system prompt)
    agent_config = AgentConfig(
        persona=PersonaConfig(
            role="Healthcare Assistant",
            goal="Help users with health queries",
            backstory="A knowledgeable medical AI assistant",
        ),
        task=TaskConfig(
            description="Answer health-related questions accurately",
            expected_output="Clear, helpful medical information",
        ),
    )

    async def main():
        agent = GenericAgent(
            agent_config=agent_config,
            llm_config=llm_config,
            tools=[],
        )

        context = ConversationContext()
        context.add_message(Message(
            role=MessageRole.USER,
            content=[TextMessage(text="What are symptoms of dehydration?")],
        ))

        result = await agent.run(context)
        print(result.llm_response.text)

    asyncio.run(main())
    ```
  </Step>

  <Step title="Run">
    ```bash theme={null}
    python my_agent.py
    ```
  </Step>
</Steps>

## With Streaming

```python theme={null}
from echo import get_llm, StreamEventType

llm = get_llm(LLMConfig(provider="openai", model="gpt-4o-mini"))

async for event in llm.invoke_stream(context, system_prompt="You are helpful."):
    if event.type == StreamEventType.TEXT:
        print(event.text, end="", flush=True)
    elif event.type == StreamEventType.DONE:
        print("\n--- Done ---")
```

## Next Steps

<CardGroup cols={2}>
  <Card title="Tools" icon="wrench" href="/ai-tools/agent-kit/tools">
    Add tools to your agent
  </Card>

  <Card title="MCP Integration" icon="plug" href="/ai-tools/agent-kit/mcp-integration">
    Connect to Eka MCP Server
  </Card>
</CardGroup>