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

> ## Agent Instructions
> The Exa API is served at https://api.exa.ai. Authenticate with `Authorization: Bearer $EXA_API_KEY` (or `x-api-key: $EXA_API_KEY`); create keys at https://dashboard.exa.ai/api-keys?utm_source=docs&utm_medium=docs&utm_campaign=markdown_instructions. Every way an agent can get access to Exa is described at https://exa.ai/auth.md.
> Prefer the official SDKs, `exa-py` (`pip install exa-py`) and `exa-js` (`npm install exa-js`); both read `EXA_API_KEY` from the environment.
> Tool-using agents can call Exa without writing code through the hosted MCP server at https://mcp.exa.ai/mcp, or install the Exa agent skill with `npx skills add exa-labs/agent-skills` (skill file: https://exa.ai/docs/skill.md).
> The OpenAPI specs at https://exa.ai/docs/exa-spec.yaml and https://exa.ai/docs/team-management-spec.yaml are the source of truth for request and response schemas.

# Sports, Weather & Places

> Find live sports data, weather forecasts, and local places with Exa Search.

Use Exa Search for live sports data, weather forecasts, and local information without integrating a separate API for each one. Ask a natural-language question with the team, place, and time window you care about.

## Write better queries

Name the location or team precisely and include a date whenever the answer changes over time. Add the condition or attribute that matters to your task instead of asking for broad information.

> [tab] Sports
>
> ### Included
>
> Available sports data:
>
> * **Scores**: games for a league on a day, including teams, scores, status, start time, and venue
> * **Standings**: current league tables with conference or division splits
> * **Schedules**: past results and upcoming games for a league or team
>
> Coverage includes the NBA, WNBA, NFL, MLB, NHL, MLS, college basketball and football, major European soccer leagues and UEFA competitions, cricket, F1, UFC, tennis, and golf.
>
> ### Ask for the league, team, and time
>
> ```text theme={null}
> NBA scores last night
> ```
>
> ```text theme={null}
> Lakers schedule this week
> ```
>
> ### Add the surrounding story
>
> Ask for the reporting you need alongside the live data.
>
> ```text theme={null}
> NBA injury reports ahead of tonight's games
> ```

> [tab] Weather
>
> ### Included
>
> Forecasts include conditions, high and low temperatures, precipitation, wind, humidity, UV index, and sunrise and sunset in the place's local time.
>
> A query with no date returns today's forecast. Ask for a specific day or range to get one page per day, up to 16 days ahead or 60 days back.
>
> ### Name the place and day
>
> ```text theme={null}
> weather in San Francisco tomorrow
> ```
>
> ### Ask about the condition that affects your plan
>
> ```text theme={null}
> will it rain in Austin this weekend
> ```
>
> ### Combine forecasts with reporting
>
> ```text theme={null}
> hurricane forecast tracks for the Gulf Coast this week
> ```

> [tab] Places
>
> ### Included
>
> * Local business profiles, with addresses, hours, amenities, and reviews
> * Venues, attractions, and points of interest
> * Real estate listings and property records
> * Zoning decisions, permits, and planning records
>
> ### Describe the place like you would ask a local
>
> Combine the category, neighborhood, and attributes that matter.
>
> ```text theme={null}
> late-night ramen in the Sunset District with outdoor seating
> ```
>
> ### Name the record type and geography
>
> ```text theme={null}
> multifamily zoning variances approved in Denver
> ```
>
> ### Compare places against practical constraints
>
> ```text theme={null}
> walkable neighborhoods in Austin with good public schools and under 30 minutes to downtown
> ```

## Make a request

All three data types use the same Search endpoint.

```python Python theme={null}
from exa_py import Exa

exa = Exa()

results = exa.search(
    "weather in San Francisco tomorrow",
    type="auto",
    num_results=5,
)
```

```javascript JavaScript theme={null}
import Exa from "exa-js";

const exa = new Exa();

const results = await exa.search("weather in San Francisco tomorrow", {
  type: "auto",
  numResults: 5,
});
```

```bash cURL theme={null}
curl -s -X POST https://api.exa.ai/search \
  -H "Authorization: Bearer $EXA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "weather in San Francisco tomorrow",
    "type": "auto",
    "numResults": 5
  }'
```

## Get structured data with Exa Agent

For structured data that requires research across multiple sources, use an [Exa Agent task run](https://exa.ai/docs/agent/quickstart.md). Describe the places, teams, dates, criteria, and output fields you need, and Agent returns schema-validated results with citations.

> [card] [Start an Agent task](https://exa.ai/docs/agent/quickstart.md)
>
> Compare places, assemble a game-day brief, or combine local details and conditions into structured results.