feat: implement MCP server and dashboard for football data platform

Add complete Nike football data platform with:
- FastMCP server exposing football data tools over HTTP
- RapidAPI client for free-api-live-football-data integration
- Bootstrap web dashboard with live match/standings views
- REST API endpoints for dashboard consumption
- Docker support with multi-stage build
- Comprehensive README with architecture docs
- Minimal .gitignore replacing verbose Python template

scripts/verify_db.py

@@ -0,0 +1,71 @@
+#!/usr/bin/env python3
+"""Quick verification of Nike DB contents."""
+import os
+
+from dotenv import load_dotenv
+import psycopg2
+
+load_dotenv('/home/robert/gitea/nike/.env')
+
+conn = psycopg2.connect(
+    host=os.getenv('DB_HOST'),
+    port=int(os.getenv('DB_PORT', 5432)),
+    user=os.getenv('DB_USER'),
+    password=os.getenv('DB_PASSWORD'),
+    dbname='nike',
+)
+cur = conn.cursor()
+
+tables = [
+    'leagues', 'teams', 'players', 'fixtures', 'standings',
+    'match_stats', 'match_events', 'player_season_stats',
+    'player_match_stats', 'followed_entities',
+]
+
+print("Nike DB Contents")
+print("-" * 40)
+for table in tables:
+    cur.execute(f"SELECT COUNT(*) FROM {table}")
+    count = cur.fetchone()[0]
+    status = "✅" if count > 0 else "•"
+    print(f"  {status}  {table:<28} {count:>6} rows")
+
+# TFC summary
+print()
+cur.execute("""
+    SELECT t.name, COUNT(p.id) AS players
+    FROM teams t
+    LEFT JOIN players p ON p.current_team_id = t.id
+    WHERE t.is_followed = TRUE
+    GROUP BY t.name
+""")
+for row in cur.fetchall():
+    print(f"  ⚽  {row[0]}: {row[1]} players in roster")
+
+cur.execute("""
+    SELECT COUNT(*) FROM fixtures f
+    JOIN teams t ON (t.id = f.home_team_id OR t.id = f.away_team_id)
+    WHERE t.is_followed = TRUE
+""")
+fix_count = cur.fetchone()[0]
+print(f"  📅  Followed team fixtures: {fix_count}")
+
+cur.execute("""
+    SELECT match_date::date, home.name, away.name, home_goals, away_goals, status
+    FROM fixtures f
+    JOIN teams home ON home.id = f.home_team_id
+    JOIN teams away ON away.id = f.away_team_id
+    JOIN teams ft ON (ft.id = f.home_team_id OR ft.id = f.away_team_id)
+    WHERE ft.is_followed = TRUE AND f.match_date >= NOW()
+    ORDER BY f.match_date ASC
+    LIMIT 3
+""")
+upcoming = cur.fetchall()
+if upcoming:
+    print()
+    print("  Next fixtures:")
+    for row in upcoming:
+        print(f"    {row[0]}  {row[1]} vs {row[2]}  ({row[5]})")
+
+cur.close()
+conn.close()