# Sports Data MCP Server - NFL, NBA, Soccer Stats, Props & Odds (`datawright/sports-data-mcp-server`) Actor

MCP server for Claude, ChatGPT, Cursor and other AI agents: live scores, schedules with betting lines, player and team game logs, NFL player props graded over/under, injuries, standings, play-by-play and rosters for 23 leagues.

- **URL**: https://apify.com/datawright/sports-data-mcp-server.md
- **Developed by:** [Datawright](https://apify.com/datawright) (community)
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 quick lookup calls

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Sports Data MCP Server - live sports stats, betting lines and player props for AI agents

Give **Claude, ChatGPT, Cursor, n8n or any MCP client** clean, current sports data: scores and schedules with **betting lines**, **player and team game logs**, **NFL, NBA, NHL and soccer player props, graded**, injuries, standings, play-by-play and rosters - for **23 leagues**: NBA, WNBA, NCAA Men's Basketball, NCAA Women's Basketball, NFL, College Football, NHL, MLB, Premier League, EFL Championship, LaLiga, Serie A, Bundesliga, Ligue 1, Eredivisie, Primeira Liga, Scottish Premiership, UEFA Champions League, UEFA Europa League, MLS, Liga MX, Brasileirao, A-League Men.

Ask things like:

- *"How has Josh Allen done against his passing-yards prop this season?"*
- *"Which NBA teams have covered the spread most often at home this month?"*
- *"Who's injured for the Chiefs, and what's the line for Sunday?"*
- *"Show me Premier League standings and Liverpool's last five results."*

### Connect

**Endpoint:** `https://datawright--sports-data-mcp-server.apify.actor/mcp` (Streamable HTTP). Authenticate with your Apify API token (Console → Settings → API & Integrations).

**Claude Code**

```bash
claude mcp add --transport http datawright-sports https://datawright--sports-data-mcp-server.apify.actor/mcp --header "Authorization: Bearer YOUR_APIFY_TOKEN"
```

**Claude Desktop / Cursor / other clients** (`mcp.json`)

```json
{
  "mcpServers": {
    "datawright-sports": {
      "url": "https://datawright--sports-data-mcp-server.apify.actor/mcp",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}
```

### Tools

| Tool | What it returns |
|---|---|
| `list_leagues` | Supported leagues and which data each offers (free) |
| `get_games` | Schedule & scores with opening vs current spread, total and moneyline |
| `get_player_game_logs` | One row per player per game: full box score, opponent, result, closing line |
| `get_team_game_logs` | Team box scores plus closing line, **ATS** and **over/under** results |
| `get_player_props` | NFL DraftKings prop lines (open/current/movement), graded against the actual stat |
| `get_prop_hit_rates` | Upcoming props with each player's last-5 / last-10 hit rate vs the line, average, streak |
| `get_injuries` | Current injury report (US leagues) |
| `get_standings` | Standings, records, streaks, point/goal differential |
| `get_play_by_play` | Play-by-play (soccer: key events) for a date |
| `get_roster` | Team roster with bio details |

Results come back as compact JSON rows (nulls removed) and are capped per call (`max_rows`, default 50, up to 500) so they fit comfortably in your model's context.

### Pricing

Pay per tool call - see the **Pricing** tab. Quick lookups (schedules, injuries, standings, rosters) cost less than data pulls (game logs, props, hit rates, play-by-play). Calls that fail are not charged. `list_leagues` is free.

### Notes

- Data comes from ESPN's public JSON feeds and DraftKings lines as published on ESPN; box scores are available minutes after a game ends.
- Need bulk exports instead (CSV/Excel, full seasons, schedules)? Use the companion dataset actors: [NFL](https://apify.com/datawright/nfl-stats-scraper), [NBA](https://apify.com/datawright/nba-stats-scraper), [Soccer](https://apify.com/datawright/soccer-stats-scraper), [all sports](https://apify.com/datawright/sports-stats-scraper).

### Disclaimer

Not affiliated with, endorsed by or connected to ESPN, DraftKings or any league. Provides publicly available factual sports statistics. It only reads publicly accessible data and grants you no rights in it: you are responsible for making sure your use complies with the data source's terms of use and applicable laws (including copyright, database and privacy laws).

# Actor input Schema

## `note` (type: `string`):

No input needed. Connect your MCP client to https://datawright--sports-data-mcp-server.apify.actor/mcp (see README). Starting a normal run performs a quick self-test.

## Actor input object example

```json
{}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("datawright/sports-data-mcp-server").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("datawright/sports-data-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call datawright/sports-data-mcp-server --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datawright/sports-data-mcp-server"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/UurEYiGcLl2fe02b6/builds/0hMYa7D1KCUmOteZ9/openapi.json