Sports MCP Server
NBA, NFL और NHL से लाइव खेल स्कोर और आँकड़े
दस्तावेज़
Sports Scores MCP — NBA, NFL & NHL for AI Agents (nexgendata/sports-mcp-server) Actor
MCP server exposing NBA, NFL, NHL and combined sports scores as agent tools. Connect Claude, Cursor, n8n or the OpenAI Agents SDK to live game scores.
- URL: https://apify.com/nexgendata/sports-mcp-server.md
- Developed by: NexGenData (community)
- Categories: MCP servers, AI, Sports
- Stats: 16 total users, 3 monthly users, 100.0% runs succeeded, 0 bookmarks
- User rating: No ratings yet
Pricing
from $20.00 / 1,000 tool 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 section below.
Each client library has reference documentation the quickstart does not restate: JavaScript/TypeScript (npm install apify-client) and Python (pip install apify-client).
README
Sports Scores MCP
A Model Context Protocol server that gives AI agents live sports scores — NBA, NFL, NHL and combined — as callable tools. For sports assistants, bots and dashboards.
📊 Sample Output
status | message | how_to_connect | server_url | apify_url | transport |
|---|---|---|---|---|---|
| MCP Server Running | This is an MCP server, not a scraper. It does not produce results whe… | Connect from an MCP-compatible AI client (Claude Desktop, Cursor, Win… | https://nexgendata--sports-mcp-server.apify.actor/mcp | https://apify.com/nexgendata/sports-mcp-server | streamable-http |
Real rows from run C3hTWLbCD6MhUUcBj on build 0.0.24 (2026-09-04), unedited apart from masked emails/phones and shortened long text; fields the source does not publish are empty.
🔧 Input reference
| Field | Type | Default | What it does |
|---|---|---|---|
enableServer (required) | boolean | true | Enable MCP server mode |
port | integer | 5000 | Port for MCP server |
🧾 JSON sample record
One real record from run C3hTWLbCD6MhUUcBj (emails/phones masked, long text shortened):
{
"status": "MCP Server Running",
"message": "This is an MCP server, not a scraper. It does not produce results when run directly.",
"how_to_connect": "Connect from an MCP-compatible AI client (Claude Desktop, Cursor, Windsurf, etc.)",
"server_url": "https://nexgendata--sports-mcp-server.apify.actor/mcp",
"apify_url": "https://apify.com/nexgendata/sports-mcp-server",
"documentation": "See the README for setup instructions and example configurations.",
"transport": "streamable-http",
"endpoint": "/mcp",
"tools": [
"get_nba_scores",
"get_nfl_scores",
"get_nhl_scores",
"get_all_scores"
]
}
💰 Pricing
| Event | Price (USD) | When it is charged |
|---|---|---|
Actor Start (apify-actor-start) | $5e-05 | Charged when the Actor starts running. Number of events charged depends on Actor memory (one event per GB, minimum one event). |
Tool call (tool-call) | $0.02 | Per-tool invocation via MCP Standby |
Pay-per-event: you pay only for what the run delivers. A run that delivers nothing bills no result events (only the actor-start event, when the actor defines one). Example: a run that delivers 100 results costs 100 × $0.02 = $2.00 plus the start fee.
🔗 Related Actors
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29 more in this family on the NexGenData Store page.
🛠 Tools (4)
get_all_scores— Scores across all supported leagues.get_nba_scores— NBA game scores.get_nfl_scores— NFL game scores.get_nhl_scores— NHL game scores.
🔌 Connect (Claude Desktop / Cursor / n8n / OpenAI Agents SDK)
Add this MCP server to your client config:
{
"mcpServers": {
"sports": {
"url": "https://nexgendata--sports-mcp-server.apify.actor/mcp"
}
}
}
Sample agent prompt:
Get today's NBA and NHL scores.
Pricing: $0.02 per tool call (Pay-Per-Event). Runs in Standby mode.
🏈 Sports MCP Server — Live NBA, NFL & NHL Scores for Claude / ChatGPT
Connect AI agents to live US sports scoreboards through the Model Context Protocol (MCP) — NBA, NFL, and NHL game scores in clean JSON tuned for LLM function-calling. A lightweight, pay-per-use alternative to monthly sports-data subscriptions for agents that just need current scores.
What You Get
This MCP server exposes 4 tools to your AI agent. Each returns the current scoreboard for its league — teams, scores, and game status (live / final / scheduled). The tools take no parameters; they return the current slate.
get_nba_scores— current NBA scoreboard (teams, scores, game status, tip-off times)get_nfl_scores— current NFL scoreboard (teams, scores, game status, kickoff times)get_nhl_scores— current NHL scoreboard (teams, scores, game status, start times)get_all_scores— NBA + NFL + NHL scoreboards in a single call, ideal for a daily sports briefing
All responses are structured JSON for LLM tool use — no HTML scraping required.
Use Cases
- Fan-engagement chatbots — Discord / Slack bots answer "what's the Lakers score?" without dev overhead
- Daily sports briefings —
get_all_scoresreturns every NBA/NFL/NHL game in one call - Sports media dashboards — auto-generate game-recap copy once a game goes final
- Twitter / X bots — post score updates from structured data instead of scraping
Quick Start
Wire this MCP server into an MCP-compatible client (Claude Desktop, Cursor, Windsurf, Cline) by pointing your config at this actor's MCP endpoint:
https://nexgendata--sports-mcp-server.apify.actor/mcp
Then ask: "What NBA games are on today and what are the scores?"
Pricing
This actor uses Apify pay-per-event pricing — you are charged per successful tool call, with no monthly subscription.
FAQ
Q: Is this an official ESPN / NBA / NFL feed? No. The server aggregates publicly available league scoreboards.
Q: Which leagues are supported? NBA, NFL, and NHL scoreboards. MLB, soccer, and other leagues are not currently supported.
Q: Can I query a specific date or a past game? No. The tools return the current scoreboard and take no parameters.
Q: Does it provide standings, player stats, schedules, or play-by-play? No. This server returns scoreboards only.
Q: Can the AI agent call this from Cursor / Cline / Claude Desktop? Yes — any MCP-compatible client works. Point your config at this actor's MCP endpoint.
About NexGenData
NexGenData publishes a catalog of Apify actors and a family of MCP servers for AI agent workflows. Browse the full catalog at https://apify.com/nexgendata
🔗 Related NexGenData Actors
- NBA Scoreboard Scraper — direct NBA scoreboard scraper (no MCP wrapper)
- NFL Scoreboard Scraper — direct NFL scoreboard scraper
- NHL Scoreboard Scraper — direct NHL scoreboard scraper
- News MCP Server — news + media monitoring for AI agents
- Finance MCP Server — finance + market data for AI agents
Actor input Schema
Actor input object example
{}
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
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("nexgendata/sports-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
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("nexgendata/sports-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
echo '{}' |
apify call nexgendata/sports-mcp-server --silent --output-dataset
MCP server setup
{
"mcpServers": {
"apify": {
"type": "http",
"url": "https://mcp.apify.com/?tools=fetch-actor-details,nexgendata/sports-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/IHlSJsgAiuJ6lJyOh/builds/kUQuzNTJeoK68jBPy/openapi.json