
Footballbin Mcp Server
- Updated January 10, 2026
- billychl1/footballbin-mcp-server
Footballbin MCP Server is an MCP server that supplies AI match predictions for Premier League and Champions League fixtures including scores, goals, and corners.
About
Footballbin MCP Server exposes football match predictions—scoped to Premier League and Champions League—with emphasis on scores, goals, and corners style outputs you can pull into an agent session. For most SaaS developers this is a specialty integration, useful when you are growing a sports newsletter, betting-adjacent analytics experiment, or fantasy community product rather than when you ship developer tooling. The value is turning model-style predictions into structured fodder your agent can summarize, compare across fixtures, or slot into content calendars. It runs as a stdio npm MCP server (v1.0.4), which makes it straightforward to wire into Claude Code or Cursor alongside your editorial prompts. Treat predictions as probabilistic signals, not financial advice; your compliance and responsible-gambling messaging stay your responsibility. If you are not in the sports vertical, skip this and pick a general analytics MCP instead.
- Match predictions for Premier League and Champions League per server description
- Surfaces scores, goals, and corners style outputs for agent-driven drafting
- stdio npm package footballbin-mcp-server v1.0.4
- Narrow vertical data MCP rather than general business analytics
Footballbin Mcp Server by the numbers
- Data as of Jul 7, 2026 (Skillselion catalog sync)
claude mcp add footballbin-mcp-server -- npx -y footballbin-mcp-serverAdd your badge
Show developers this MCP server is listed on Skillselion. Paste this into your README.
| Package | footballbin-mcp-server |
|---|---|
| Transport | STDIO |
| Auth | None |
| Last updated | January 10, 2026 |
| Repository | billychl1/footballbin-mcp-server ↗ |
What it does
Pull AI-style Premier League and Champions League match predictions (scores, goals, corners) into an agent workflow for sports content or analytics side projects.
Who is it for?
Best when you're running football prediction blogs, newsletters, Discord bots, or fantasy helper apps tied to PL and UCL.
Skip if: General SaaS founders who need product analytics, revenue metrics, or non-sports data pipelines.
What you get
After you connect Footballbin, your agent can fetch prediction-style match data and speed up content production for football-focused channels.
- Agent-accessible PL and UCL match prediction outputs
- Structured signals for scores, goals, and corners oriented content drafts
By the numbers
- Server version 1.0.4 on npm identifier footballbin-mcp-server
- Catalog description cites Premier League and Champions League coverage
README.md
FootballBin MCP Server
A Model Context Protocol (MCP) server that provides AI agents with access to football match predictions for the Premier League and Champions League.
Requirements
- Node.js 18+ (check with
node --version)
Installation
Option 1: npm (Recommended)
npm install -g footballbin-mcp-server
Option 2: npx (No Install)
npx footballbin-mcp-server
Option 3: Remote Endpoint
No installation required - use the hosted endpoint directly:
https://ru7m5svay1.execute-api.eu-central-1.amazonaws.com/prod/mcp
Quick Start
Claude.ai (Easiest - No Install)
- Go to Settings > Connectors
- Click Add custom connector
- Enter:
https://ru7m5svay1.execute-api.eu-central-1.amazonaws.com/prod/mcp
Claude Desktop
Requires Node.js 18+
Step 1: Install globally
npm install -g footballbin-mcp-server
Step 2: Find your Node.js path (must be v18+)
which node && node --version
Step 3: Add to claude_desktop_config.json:
{
"mcpServers": {
"footballbin": {
"command": "/path/to/node",
"args": ["/path/to/node_modules/footballbin-mcp-server/dist/index.js"]
}
}
}
Example configs:
macOS with nvm:
{
"mcpServers": {
"footballbin": {
"command": "/Users/YOU/.nvm/versions/node/v20.x.x/bin/node",
"args": ["/Users/YOU/.nvm/versions/node/v20.x.x/lib/node_modules/footballbin-mcp-server/dist/index.js"]
}
}
}
macOS with Homebrew:
{
"mcpServers": {
"footballbin": {
"command": "/opt/homebrew/bin/node",
"args": ["/opt/homebrew/lib/node_modules/footballbin-mcp-server/dist/index.js"]
}
}
}
Windows:
{
"mcpServers": {
"footballbin": {
"command": "C:\\Program Files\\nodejs\\node.exe",
"args": ["C:\\Users\\YOU\\AppData\\Roaming\\npm\\node_modules\\footballbin-mcp-server\\dist\\index.js"]
}
}
}
Config file location:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
Other MCP Clients
Use the remote endpoint:
https://ru7m5svay1.execute-api.eu-central-1.amazonaws.com/prod/mcp
Features
AI Match Predictions:
- Half-time score
- Full-time score
- Next goal scorer
- Corner count predictions
Supported Leagues:
- Premier League (EPL)
- UEFA Champions League (UCL)
Key Players: Each match includes key player insights with reasoning
Tool: get_match_predictions
Input Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
league |
string | Yes | premier_league, epl, pl, champions_league, ucl, cl |
matchweek |
number | No | Matchweek number (defaults to current) |
home_team |
string | No | Filter by home team (e.g., chelsea, arsenal) |
away_team |
string | No | Filter by away team (e.g., liverpool, wolves) |
Team Aliases
| Alias | Maps To |
|---|---|
united, mufc |
man_utd |
city, mcfc |
man_city |
spurs |
tottenham |
villa |
aston_villa |
forest |
nottm_forest |
palace |
crystal_palace |
gunners |
arsenal |
reds |
liverpool |
blues |
chelsea |
barca |
barcelona |
real |
real_madrid |
Example Response
{
"league": "premier_league",
"matchweek": 22,
"count": 10,
"app_link": "https://apps.apple.com/app/footballbin/id6757111871",
"matches": [
{
"match_id": "epl_mw22_liv_bur",
"home_team": "Liverpool",
"away_team": "Burnley",
"kickoff_time": "2026-01-17T15:00:00Z",
"status": "scheduled",
"predictions": [
{ "type": "Half Time Result", "value": "2:0", "confidence": 75 },
{ "type": "Full Time Result", "value": "4:0", "confidence": 75 },
{ "type": "Next Goal", "value": "Home,Wirtz", "confidence": 75 },
{ "type": "Corner Count", "value": "9:3", "confidence": 75 }
],
"key_players": [
{
"player_name": "Florian Wirtz",
"reason": "12 goals, 14 assists. Liverpool's creative hub."
}
]
}
]
}
Direct API Usage
List Tools
curl -X POST https://ru7m5svay1.execute-api.eu-central-1.amazonaws.com/prod/mcp \
-H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","method":"tools/list","id":1}'
Get Predictions
curl -X POST https://ru7m5svay1.execute-api.eu-central-1.amazonaws.com/prod/mcp \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"name": "get_match_predictions",
"arguments": {"league": "premier_league"}
},
"id": 1
}'
Registry Links
- npm: https://www.npmjs.com/package/footballbin-mcp-server
- Official MCP Registry: https://registry.modelcontextprotocol.io
- GitHub: https://github.com/billychl1/footballbin-mcp-server
FootballBin App
Get the full experience with the FootballBin iOS app:
Features:
- Live match tracking
- AI player valuations
- Detailed match predictions
- Player news and discussions
Technical Details
- Protocol: JSON-RPC 2.0 / MCP
- Transport: stdio (npm) or HTTPS (remote)
- Runtime: Node.js 20+
Error Codes
| Code | Meaning |
|---|---|
| -32700 | Parse error |
| -32600 | Invalid request |
| -32601 | Method not found |
| -32602 | Invalid params |
License
MIT License - see LICENSE file.
Links
Recommended MCP Servers
How it compares
Vertical sports prediction data MCP, not a general web research or business intelligence server.
FAQ
Who is Footballbin MCP Server for?
Creators and developers building football-focused content or lightweight prediction experiences around Premier League and Champions League matches.
When should I use Footballbin MCP Server?
Use it when you publish regular match previews or community updates and want your agent to pull structured prediction signals instead of hand-researching fixtures.
How do I add Footballbin MCP Server to my agent?
Add the footballbin-mcp-server npm package (v1.0.4) to your MCP client’s stdio configuration and call its tools from prompts that need PL/UCL prediction data.