> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Exa Search Tool

> Guide for using the Exa Search tool with PraisonAI agents.

The Exa Search tool lets an agent run neural web search and retrieve page contents through the Exa API.

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    subgraph "Exa Search"
        User[User] --> Agent[Agent]
        Agent --> Tool[search_and_contents]
        Tool --> API[Exa API]
        API --> Result[Results]
    end

    classDef input fill:#8B0000,stroke:#7C90A0,color:#fff
    classDef process fill:#189AB4,stroke:#7C90A0,color:#fff
    classDef output fill:#10B981,stroke:#7C90A0,color:#fff

    class User,Agent input
    class Tool,API process
    class Result output
```

## Overview

The Exa Search tool is a tool that allows you to search the web and retrieve content using the Exa API.

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
pip install praisonaiagents exa-py
export EXA_API_KEY="${EXA_API_KEY:?Set EXA_API_KEY in your shell}"
export OPENAI_API_KEY="${OPENAI_API_KEY:?Set OPENAI_API_KEY in your shell}"
```

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import Agent, AgentTeam
from exa_py import Exa
import os

exa = Exa(api_key=os.environ["EXA_API_KEY"])

def search_and_contents(query: str):
    """Search for webpages based on the query and retrieve their contents."""
    # This combines two API endpoints: search and contents retrieval
    return str(exa.search_and_contents(
        query, use_autoprompt=False, num_results=5, text=True, highlights=True
    ))

data_agent = Agent(instructions="Find the latest jobs for Video Editor in New York at startups", tools=[search_and_contents])
editor_agent = Agent(instructions="Curate the available jobs at startups and their email for the candidate to apply based on his skills on Canva, Adobe Premiere Pro, and Adobe After Effects")
agents = AgentTeam(agents=[data_agent, editor_agent], process='hierarchical')
agents.start()
```

## How It Works

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sequenceDiagram
    participant User
    participant Agent
    participant Exa as search_and_contents
    participant API as Exa API

    User->>Agent: "Search for X"
    Agent->>Exa: search_and_contents(query)
    Exa->>API: search + contents request
    API-->>Exa: results with text
    Exa-->>Agent: parsed result
    Agent-->>User: final answer
```

## Getting Started

<Steps>
  <Step title="Simple Usage">
    1. Install dependencies (see **Overview** above)
    2. Set required API keys in your environment
    3. Run the agent example in **Overview**
  </Step>

  <Step title="With Configuration">
    Use the same tool with an agent — see the **Overview** example, or pass env vars from the sections above.
  </Step>
</Steps>

## Best Practices

<AccordionGroup>
  <Accordion title="Keep the API key in the environment">
    Read the key with `os.environ["EXA_API_KEY"]` and set it in your shell or `.env`. Never hard-code it in the tool function.
  </Accordion>

  <Accordion title="Cap num_results">
    `search_and_contents` accepts `num_results=5`. Keep it low so the agent processes fewer tokens — raising it retrieves full page text for every hit.
  </Accordion>

  <Accordion title="Handle rate limits">
    Exa returns HTTP 429 when the plan quota is exceeded. Wrap the call in `try/except` so the agent can fall back to another search tool instead of crashing.
  </Accordion>
</AccordionGroup>

## Related Tools

<CardGroup cols={2}>
  <Card title="Exa" icon="book" href="/docs/tools/external/exa">
    Neural search (praisonai-tools)
  </Card>

  <Card title="Tavily" icon="book" href="/docs/tools/external/tavily">
    AI-powered search
  </Card>

  <Card title="Serper" icon="book" href="/docs/tools/external/serper">
    Google search API
  </Card>
</CardGroup>