football-data-mcp

football-data-mcp

Provides football analytics tools including player scouting, comparisons, market-value filters, expected-goals tables, match-by-match form, team attacking profiles, match search, shot maps, and more for 10 leagues.

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README

football-data-mcp

A football analytics toolkit for Claude (and similar LLM tools) — player scouting, comparisons, market-value filters, expected-goals tables, match-by-match form, team attacking profiles, match search, shot maps, and more.

Built on top of ScraperFC by Owen Seymour.


What it does

Combines player and match statistics into one dataset you can explore in conversation with Claude.

Coverage: 10 leagues · 3 seasons (2023-24, 2024-25, 2025-26) · 18,800+ player records

Season stats (one row per player per season):

Kind of data Where it’s available
Goals, assists, minutes, shots, cards All 10 leagues
Expected goals (xG), non-penalty xG, expected assists All 10 leagues — richest in the top five European leagues
Build-up xG (how much a player contributes before a shot) Top five leagues only (England, Spain, Germany, Italy, France)
Advanced passing & chance creation Top five + Netherlands + Portugal — not Championship or European cups
Player ratings, duels, dribbles, big chances, and 80+ other performance metrics All 10 leagues
Market value, contract end date, height, nationality Domestic leagues — weakest for Champions League and Europa League

Match-by-match stats (optional extra step when collecting data):

Kind of data Where it’s available
Last N games, form, ratings, shot locations, team xG for/against All 10 leagues (after match data is collected)
League tables ranked by xG (home / away / overall) Top five leagues only

Leagues covered

All leagues include three seasons: 2023-24, 2024-25, and 2025-26.

League Season-level data Match-by-match
England Premier League Full — xG, build-up, advanced passing, ratings, market value Yes
Spain La Liga Full Yes
Germany Bundesliga Full Yes
Italy Serie A Full Yes
France Ligue 1 Full Yes
Netherlands Eredivisie Strong — xG, advanced passing, ratings, market value (no build-up xG) Yes
Portugal Primeira Liga Strong Yes
England EFL Championship Basic — ratings and core stats; lighter xG; market value often available Yes
UEFA Champions League Basic — ratings and core stats; no market value Yes
UEFA Europa League Basic — ratings and core stats; no market value Yes

Full = goals and minutes, full xG suite including build-up, advanced passing metrics, player ratings, and market value.

Strong = same as Full except build-up xG.

Basic = goals, minutes, player ratings, and xG-style metrics; limited advanced passing; European cups lack market value.

Market value and contract data are most complete for the eight main domestic leagues (all except Championship and the two European cups).


The 16 tools

Once connected, Claude can answer questions using 16 built-in tools.

Season-level player data

Tool What you can ask
get_player "Show me everything on Bukayo Saka"
scout_position "Top 10 forwards in the Bundesliga this season by xG"
compare_players "Compare Salah and Son across all stats"
find_similar_players "Find players similar to Bellingham under €80m"
get_league_table "xG league table for Serie A, home games only" (top five leagues)
get_match Shot map and line-ups for a specific match (top five leagues)
get_sofascore_match Deep stats for one fixture — players, teams, shots
get_club_elo "How strong is Real Madrid right now?"
get_player_history Per-match form (xG, goals, assists) from Understat; TM value/contract via get_player
data_status What data you have loaded and how complete it is

Match-by-match analytics

Requires match data to be collected first. Works across all 10 leagues.

Tool What you can ask
get_player_match_log "Salah's last 10 Premier League matches with ratings and xG"
get_player_form "Haaland's average rating and xG per 90 over recent games"
get_team_stats "Arsenal's average xG for and against this season"
compare_teams "Compare Liverpool and Man City on xG and possession"
search_matches "High-xG Premier League games this season"
get_player_shot_map "Shot locations and xG for Kane in the Bundesliga"

Setup

Everything runs on your computer: download the stats, then connect Claude Desktop or Cursor so it can answer questions using the 16 tools.

1. Install

pip install football-data-mcp

That installs two commands you can run from any folder:

  • collect-data — downloads and builds the dataset
  • soccer-mcp — starts the connection Claude and Cursor use

Working on the code? Clone this repo and run pip install -e . in the project folder instead.

2. Collect the data

First-time full download takes a while (some sites open a headless browser in the background).

Stats are collected from Understat, SofaScore, ClubElo, Transfermarkt, and Capology (see CHANGELOG.md for recent pipeline changes).

collect-data

Useful shortcuts:

# Only refresh one part of the data
collect-data --sofascore-only
collect-data --understat-only
collect-data --transfermarkt-only

# Extra: league xG tables, match shots, line-ups
collect-data --understat-tables-only
collect-data --understat-matches-only

# Rebuild the merged player file from files you already downloaded
collect-data --rebuild-only
collect-data --rebuild-only --export-csv   # also write a spreadsheet copy

3. Connect Claude Desktop or Cursor

Add the data connection to your app’s config. After pip install, soccer-mcp should be on your PATH (same program as python3 -m soccer_server).

Claude Desktop (macOS config file):

~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "soccer-data": {
      "command": "soccer-mcp"
    }
  }
}

Cursor~/.cursor/mcp.json or .cursor/mcp.json in a project:

{
  "mcpServers": {
    "soccer-data": {
      "command": "soccer-mcp"
    }
  }
}

If the app cannot find soccer-mcp, use the full path from which soccer-mcp as "command", or:

"command": "python3",
"args": ["-m", "soccer_server"]

Quit and reopen Claude or Cursor after saving. You should see all 16 tools after step 2 has finished downloading data.

<!--

Hosted service (coming later) — mcp.kupsas.com

Use the managed MCP endpoint (no local scraping). You need an API key and a short client config.

Endpoint: https://mcp.kupsas.com/football-data/mcp
Health check: https://mcp.kupsas.com/football-data/health

Get an API key

Until a web dashboard ships (platform.kupsas.com), mint a key from the terminal:

  1. Sign in to the hosted Supabase project (Google SSO or email) and obtain a short-lived access JWT (Supabase Auth token endpoint or your app).
  2. Exchange it for a long-lived MCP API key:
export SUPABASE_JWT="paste-your-supabase-access-token-here"

curl -sS -X POST "https://mcp.kupsas.com/football-data/api/keys" \
  -H "Authorization: Bearer $SUPABASE_JWT" \
  -H "Content-Type: application/json" \
  -d '{"name":"my-laptop"}'

Copy the "key" from the JSON response once — it cannot be retrieved again. Store it in a password manager or an env var (do not commit it to git).

export FOOTBALL_MCP_API_KEY="paste-key-here"

Cursor (recommended — native HTTPS)

Edit ~/.cursor/mcp.json (or .cursor/mcp.json in a repo):

{
  "mcpServers": {
    "football-hosted": {
      "url": "https://mcp.kupsas.com/football-data/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_MCP_API_KEY"
      }
    }
  }
}

Restart Cursor → Settings → MCP should show connected and list tools. In Agent chat, name tools explicitly when needed, e.g. “Use the get_league_table MCP tool for England Premier League 2024-2025.”

Claude Desktop (requires mcp-remote bridge)

Claude Desktop does not support "url" / remote HTTP in config — only local subprocesses. Use mcp-remote so Claude talks stdio to a local bridge that calls HTTPS:

{
  "mcpServers": {
    "football-hosted": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.kupsas.com/football-data/mcp",
        "--header",
        "Authorization: Bearer YOUR_MCP_API_KEY"
      ]
    }
  }
}

Requires Node.js / npx. Quit Claude completely (Cmd+Q), reopen, wait for first-time npx download. Logs: ~/Library/Logs/Claude/mcp*.log.

Verify from the terminal (optional)

curl -sS "https://mcp.kupsas.com/football-data/health" | python3 -m json.tool

curl -sS -X POST "https://mcp.kupsas.com/football-data/mcp" \
  -H "Authorization: Bearer $FOOTBALL_MCP_API_KEY" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05","capabilities":{},"clientInfo":{"name":"curl","version":"1.0"}}}'

Expect HTTP 200 (401 = bad key; 406 = server needs json_response=True — contact the operator).

Hosted troubleshooting (short)

Issue Fix
Claude: server missing Use mcp-remote config above, not "type": "http"
401 Mint a new key; check Bearer prefix
Cursor: connected but no tool use Agent mode; mention tool name in the prompt

More detail for operators: private deploy docs (Phase 6 + client §9).

-->

Contributing

This project builds on ScraperFC. Bug fixes to the underlying scrapers are contributed back upstream — if you find something broken in a scraper, consider opening an issue or PR there too.

For issues specific to the pipeline (collect_data package / collect-data / collect_data.py) or the MCP server (soccer_server package / soccer-mcp / python -m soccer_server), open an issue here.


Credits

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