# Livetennisapi MCP Integration > Integrate Live Tennis API MCP server to give AI agents real-time tennis scores, odds, and win probabilities - Skill: `aradotso/livetennisapi-mcp-integration` (Agent Skill) - Install (CLI): `npx skillmds@latest add aradotso/livetennisapi-mcp-integration` - Raw SKILL.md: https://api.skillmd.com/api/skills/aradotso/livetennisapi-mcp-integration/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: aradotso (https://skillmd.com/u/aradotso) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/aradotso/livetennisapi-mcp-integration --- # livetennisapi-mcp Integration > Skill by [ara.so](https://ara.so) — MCP Skills collection. The **livetennisapi-mcp** server provides AI agents with access to real-time tennis data through the Model Context Protocol (MCP). It exposes 12 tools for querying live scores, upcoming matches, player profiles, odds, and ML-powered win probabilities across ATP, WTA, Challenger, and ITF tournaments. ## Installation ### Get an API Key 1. Visit [livetennisapi.com/subscribe/free](https://livetennisapi.com/subscribe/free) for a free key (no credit card) 2. Store your key in an environment variable: ```bash export LIVETENNISAPI_KEY=twjp_your_actual_key_here ``` ### Claude Code ```bash claude mcp add livetennis -e LIVETENNISAPI_KEY=twjp_your_key -- npx -y livetennisapi-mcp ``` ### Claude Desktop Add to `claude_desktop_config.json`: ```json { "mcpServers": { "livetennis": { "command": "npx", "args": ["-y", "livetennisapi-mcp"], "env": { "LIVETENNISAPI_KEY": "twjp_your_key_here" } } } } ``` **Config file locations:** - macOS: `~/Library/Application Support/Claude/claude_desktop_config.json` - Windows: `%APPDATA%\Claude\claude_desktop_config.json` - Linux: `~/.config/Claude/claude_desktop_config.json` ### Cursor / Zed Same configuration pattern as Claude Desktop. Add the server block to your MCP settings file. ### Codex ```bash codex mcp add livetennisapi \ --url https://mcp.livetennisapi.com/mcp \ --bearer-token-env-var LIVETENNISAPI_KEY ``` Or manually in `~/.codex/config.toml`: ```toml [mcp_servers.livetennisapi] url = "https://mcp.livetennisapi.com/mcp" bearer_token_env_var = "LIVETENNISAPI_KEY" ``` ## Available Tools ### FREE Tier | Tool | Purpose | |------|---------| | `get_live_matches` | All matches currently in progress with live scores | | `get_upcoming_matches` | Matches starting soon | | `get_match` | Full details for a specific match | | `get_match_score` | Just the score (fastest) | | `search_players` | Find players by name | | `get_player` | Player profile, ranking, country, handedness | | `get_fixtures` | Forward schedule | ### BASIC Tier - `get_recent_results` — Completed matches and winners ### PRO Tier - `get_match_events` — Breaks, games, sets, momentum shifts - `get_match_odds` — Match-winner betting prices (bid/ask/mid) ### ULTRA Tier - `get_match_analysis` — ML model win probability and key factors ### Utility - `check_api_status` — Verify API connectivity and key tier ## Usage Patterns ### Checking Live Matches **User prompt:** ``` What tennis matches are live right now? ``` The agent will call `get_live_matches` and receive structured data: ```json { "matches": [ { "match_id": 18953, "tournament": "Australian Open", "round": "QF", "player1": "Carlos Alcaraz", "player2": "Jannik Sinner", "score": "6-3, 2-4", "serving": 2, "status": "live" } ] } ``` ### Player Lookup **User prompt:** ``` Show me Sinner's ranking and recent results ``` The agent will: 1. Call `search_players` with query "Sinner" 2. Call `get_player` with the player_id 3. Call `get_recent_results` (if key has BASIC+) ```json { "player_id": 12345, "name": "Jannik Sinner", "country": "ITA", "ranking": 1, "ranking_points": 11830, "handedness": "right", "age": 23 } ``` ### Match Details with Odds **User prompt:** ``` What are the odds on the Alcaraz vs Sinner match? ``` For PRO+ keys, the agent calls: 1. `get_live_matches` or `get_match` to find match_id 2. `get_match_odds` with that match_id ```json { "match_id": 18953, "player1_odds": { "bid": 1.85, "ask": 1.90, "mid": 1.875 }, "player2_odds": { "bid": 1.95, "ask": 2.00, "mid": 1.975 } } ``` ### Win Probability Analysis **User prompt:** ``` What does the model give Alcaraz in this match? ``` For ULTRA keys, the agent calls `get_match_analysis`: ```json { "match_id": 18953, "player1_win_probability": 0.48, "player2_win_probability": 0.52, "key_factors": [ "Sinner's serve hold rate on hard courts: 89%", "Alcaraz's recent injury recovery affecting movement" ], "model_thesis": "Close match. Sinner slight favorite due to surface advantage." } ``` ## Tier-Aware Responses The server returns **human-readable explanations** instead of raw 403 errors when a tool requires a higher tier: ``` This data requires the PRO plan, and the configured API key is on FREE tier. Upgrade at https://livetennisapi.com/#pricing ``` This prevents the agent from hallucinating reasons or retrying endlessly. ### Check Your Key's Tier ``` What tier is my API key on? ``` The agent calls `check_api_status`, which probes upward to determine: ```json { "status": "reachable", "tier": "PRO", "message": "API is reachable. Your key is on the PRO plan." } ``` ## HTTP Endpoint (Alternative) For clients that cannot run stdio MCP servers, use the hosted HTTP endpoint: ``` https://mcp.livetennisapi.com/mcp ``` ### With Claude Messages API (Python) ```python import os import anthropic client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"]) response = client.beta.messages.create( model="claude-opus-4-8", max_tokens=4096, betas=["mcp-client-2025-11-20"], mcp_servers=[{ "type": "url", "name": "livetennisapi", "url": "https://mcp.livetennisapi.com/mcp", "authorization_token": os.environ["LIVETENNISAPI_KEY"], }], tools=[{"type": "mcp_toolset", "mcp_server_name": "livetennisapi"}], messages=[{ "role": "user", "content": "What tennis matches are live right now?" }], ) print(response.content) ``` ### With Claude Web Connector Add a custom connector in Claude with: ``` https://mcp.livetennisapi.com/mcp?token=twjp_your_key ``` **Security note:** Prefer `Authorization: Bearer` header over `?token=` when your client supports it. The query param exists for clients that cannot set headers. ## Development & Self-Hosting ### Local Development ```bash git clone https://github.com/livetennisapi/livetennisapi-mcp.git cd livetennisapi-mcp npm install npm run build # Run stdio server LIVETENNISAPI_KEY=twjp_your_key node dist/index.js # Run HTTP server (port 8081) LIVETENNISAPI_KEY=twjp_your_key node dist/http.js ``` ### Testing ```bash npm test # Protocol + transport isolation + rate limiting npm run test:mutation # Proves tests fail when code breaks ``` The mutation tests are important: they reintroduce bugs the tests claim to catch and verify the suite actually detects them. ### Self-Host HTTP Endpoint See `deploy/install-http.sh` and `deploy/TUNNEL.md` in the repository for instructions on running your own HTTP endpoint. The hosted endpoint is **multi-tenant** and holds no key of its own — every request builds an isolated server bound to the key provided in that request. ## Troubleshooting ### "Server not found" or "Connection refused" **Stdio version:** - Ensure `npx` can reach npm registry: `npx -y livetennisapi-mcp --version` - Check Node.js version: `node --version` (needs 18+) - Restart your AI client after adding the server config **HTTP version:** - Verify endpoint is reachable: `curl https://mcp.livetennisapi.com/mcp` - Check firewall/proxy settings ### "Invalid API key" or 401 errors ```bash # Verify your key is set correctly echo $LIVETENNISAPI_KEY # Test key directly against API curl -H "Authorization: Bearer $LIVETENNISAPI_KEY" \ https://api.livetennisapi.com/v1/live_matches ``` If the curl works but MCP doesn't, the env var isn't reaching the server process. In Claude Desktop, ensure `env` is in the server config, not at the root level. ### "upgrade_required" responses Your key works, but the endpoint requires a higher tier. Use `check_api_status` to see your current tier, then upgrade at [pricing](https://livetennisapi.com/#pricing). ### Rate limiting - Anonymous requests to HTTP endpoint: 60/minute - Keyed requests to HTTP endpoint: 300/minute - Per-key quotas enforced upstream by tier If you hit the limit, the server returns a 429 with `Retry-After` header. ### No live matches returned Tennis is not 24/7. Grand Slams and peak season provide the most coverage. If `get_live_matches` returns an empty array, try `get_upcoming_matches` or `get_fixtures` to see the schedule. ## Code Examples ### TypeScript: Using the Underlying Client The MCP server is built on the official `livetennisapi` client. You can use it directly: ```typescript import { LiveTennisAPI } from 'livetennisapi'; const client = new LiveTennisAPI(process.env.LIVETENNISAPI_KEY!); // Get live matches const liveMatches = await client.getLiveMatches(); console.log(liveMatches); // Search for a player const players = await client.searchPlayers('Djokovic'); const playerId = players[0]?.player_id; // Get player details if (playerId) { const player = await client.getPlayer(playerId); console.log(`${player.name} is ranked #${player.ranking}`); } // Get match odds (PRO tier) const odds = await client.getMatchOdds(18953); console.log(`Player 1 mid: ${odds.player1_odds.mid}`); ``` ### JavaScript: Programmatic MCP Tool Calls ```javascript import { Client } from '@modelcontextprotocol/sdk/client/index.js'; import { StdioClientTransport } from '@modelcontextprotocol/sdk/client/stdio.js'; const transport = new StdioClientTransport({ command: 'npx', args: ['-y', 'livetennisapi-mcp'], env: { LIVETENNISAPI_KEY: process.env.LIVETENNISAPI_KEY } }); const client = new Client({ name: 'tennis-client', version: '1.0.0' }, { capabilities: {} }); await client.connect(transport); // List available tools const { tools } = await client.listTools(); console.log(tools.map(t => t.name)); // Call a tool const result = await client.callTool({ name: 'get_live_matches', arguments: {} }); console.log(result.content); ``` ## Related Projects - **Python client:** `pip install livetennisapi` — [livetennisapi-python](https://github.com/livetennisapi/livetennisapi-python) - **JavaScript client:** `npm install livetennisapi` — [livetennisapi-js](https://github.com/livetennisapi/livetennisapi-js) - **Vercel AI SDK tools:** `npm install livetennisapi-ai` — [livetennisapi-ai](https://github.com/livetennisapi/livetennisapi-ai) - **OpenAPI spec:** [livetennisapi/openapi](https://github.com/livetennisapi/openapi) ## Resources - **API Documentation:** [docs.livetennisapi.com](https://docs.livetennisapi.com) - **Pricing & Plans:** [livetennisapi.com/#pricing](https://livetennisapi.com/#pricing) - **Terms of Service:** [livetennisapi.com/terms](https://livetennisapi.com/terms) - **Support:** Open an issue at [github.com/livetennisapi/livetennisapi-mcp](https://github.com/livetennisapi/livetennisapi-mcp)