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fpl-mcp-server

fpl-mcp-server

Local
github.com/nguyenanhducsGames & Entertainment1Updated 36w ago

About fpl-mcp-server

fpl-mcp-server provides analysis and strategy tools for Fantasy Premier League players who want to examine players, fixtures, and manager data. It combines tools, data resources, and strategy prompts, with fuzzy matching and transfer-trend lookup.

Key features

  1. 01Search players and analyze fixtures
  2. 02Compare managers, squads, and transfers
  3. 03Access player, team, and gameweek resources
  4. 04Use prompts for squad and transfer planning
  5. 05Match player names fuzzily
  6. 06Track current-gameweek transfer trends

Use cases

  1. 01Analyze a gameweek and plan a lineup
  2. 02Time transfers around fixture runs
  3. 03Compare manager squads and transfer activity
  4. 04Find players despite nicknames or spelling variants

MCP support

The MCP server gives clients 19 tools, four data resources, and 10 strategy prompts for Fantasy Premier League analysis.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"nguyenanhducs-fpl": {
"command": "uvx",
"args": [
"fpl-mcp-server"
]
}
}
}
Run commanduvx fpl-mcp-server

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypifpl-mcp-server1.0.3

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

Fantasy Premier League MCP Server

A comprehensive Model Context Protocol (MCP) server for Fantasy Premier League analysis and strategy. This server provides AI assistants with powerful tools, resources, and prompts to help you dominate your FPL mini-leagues with data-driven insights.

PyPI Python 3.13+ License: MIT MCP Document

Features

This MCP server provides comprehensive FPL analysis capabilities through:

  • 19 Interactive Tools - Search players, analyze fixtures, compare managers, track transfers, and more
  • 4 Data Resources - access to players, teams, gameweeks, and current gameweek bootstrap data
  • 10 Strategy Prompts - Structured templates for gameweek analysis, squad analysis, transfer planning, chip strategy, lineup selection, and captain selection
  • Smart Caching - 4-hour cache for bootstrap data to minimize API calls while keeping data fresh
  • Fuzzy Matching - Find players even with spelling variations or nicknames
  • Live Transfer Trends - Track the most transferred in/out players for current gameweek
  • Manager Insights - Analyze squads, transfers, and chip usage
  • Fixture Analysis - Assess team fixtures and plan transfers around favorable runs

Quick Start

Option 1: uvx (Recommended)

The fastest way to get started - no installation required:

{
  "mcpServers": {
    "fpl": {
      "command": "uvx",
      "args": ["fpl-mcp-server"],
      "type": "stdio"
    }
  }
}
Option 2: Docker

Use the official Docker image from GitHub Container Registry:

{
  "mcpServers": {
    "fpl": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "ghcr.io/nguyenanhducs/fpl-mcp-server:latest"
      ],
      "type": "stdio"
    }
  }
}

For detailed installation instructions and more options, see Installation Guide.

Usage & Documentation

Once configured, you can interact with the FPL MCP server through Claude Desktop using natural language.

For detailed guidance, see:

Data Sources

This server uses the official Fantasy Premier League API, see here for more details.

Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.