Fantasy Premier League MCP Server

What does “Fantasy Premier League” MCP Server do?

The Fantasy Premier League MCP (Model Context Protocol) Server connects AI assistants to the official Fantasy Premier League (FPL) data, enabling seamless integration with the FPL ecosystem. By acting as a bridge between AI agents and the FPL API or datasets, this server provides real-time access to player statistics, team data, and other FPL resources. This integration empowers developers and AI workflows to automate tasks such as fetching team info, analyzing player performance, or generating lineup suggestions. As part of the Model Context Protocol, it standardizes access to FPL data, making it easier for AI clients to interact with complex football data, streamline FPL management, and enhance user engagement with AI-driven insights.

List of Prompts

No prompt templates were found in the repository or documentation.

List of Resources

No explicit resources were documented in the available files.

List of Tools

No server.py file or explicit tool definitions were found in the repository.

Use Cases of this MCP Server

• Automated Team Data Retrieval: AI agents can fetch up-to-date team and player information from the official Fantasy Premier League database.
• Player Performance Analysis: Developers can build AI workflows that analyze historical and real-time player stats for prediction or recommendation purposes.
• Lineup Optimization: Enable AI to suggest optimal lineups based on fixtures, injuries, and player statistics.
• League Management Automation: Streamline league data collection, standings, and performance tracking for FPL mini-leagues.
• Content Generation: Power AI-driven content such as weekly previews, reviews, or transfer advice using official FPL data.

How to set it up

Windsurf

1. Ensure Node.js and Windsurf are installed on your system.
2. Locate your Windsurf configuration file (e.g., windsurf.config.json).
3. Add the Fantasy Premier League MCP Server to the mcpServers section:

   {
     "mcpServers": {
       "fantasy-pl-mcp": {
         "command": "fantasy-pl-mcp",
         "args": ["--port", "4137"]
       }
     }
   }
   

4. Save the configuration and restart Windsurf.
5. Verify the server is running by checking the Windsurf server logs.

Claude

1. Install Node.js and the Claude platform.
2. Open the Claude configuration file.
3. Add the Fantasy Premier League MCP Server:

   {
     "mcpServers": {
       "fantasy-pl-mcp": {
         "command": "fantasy-pl-mcp",
         "args": ["--port", "4137"]
       }
     }
   }
   

4. Save the changes and restart Claude.
5. Confirm the setup in the Claude dashboard.

Cursor

1. Ensure you have Node.js and Cursor installed.
2. Edit the cursor.config.json file.
3. Insert the MCP server in the mcpServers definition:

   {
     "mcpServers": {
       "fantasy-pl-mcp": {
         "command": "fantasy-pl-mcp",
         "args": ["--port", "4137"]
       }
     }
   }
   

4. Save and restart Cursor.
5. Check for server availability in the Cursor interface.

Cline

1. Make sure Node.js and Cline are installed.
2. Update your Cline configuration file.
3. Add the Fantasy Premier League MCP Server:

   {
     "mcpServers": {
       "fantasy-pl-mcp": {
         "command": "fantasy-pl-mcp",
         "args": ["--port", "4137"]
       }
     }
   }
   

4. Save the file and restart Cline.
5. Verify the server is operational in the Cline environment.

Securing API Keys

To secure API keys, use environment variables in your configuration. Example:

{
  "mcpServers": {
    "fantasy-pl-mcp": {
      "command": "fantasy-pl-mcp",
      "args": ["--port", "4137"],
      "env": {
        "FPL_API_KEY": "${FPL_API_KEY}"
      },
      "inputs": {
        "api_key": "${FPL_API_KEY}"
      }
    }
  }
}

Replace FPL_API_KEY with your actual environment variable name.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "fantasy-pl-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change "fantasy-pl-mcp" to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Our opinion

This MCP server offers a clear FPL integration and provides solid setup instructions but lacks documentation on prompts, resources, and tools. Its open-source status and modest community activity are positives, but the absence of customizable or advanced features limits its utility for broader AI workflows.

Score: 4/10

MCP Score