Fantasy Premier League MCP Server

The Fantasy Premier League MCP Server is a dedicated bridge between the rich, real‑time data of the English Football League and AI assistants that support the Model Context Protocol. It solves a common pain point for developers and sports enthusiasts: accessing up‑to‑date player statistics, team rosters, and gameweek information without having to write custom API wrappers or handle authentication tokens. By exposing a set of well‑defined tools—such as player search, comparison, and gameweek status—the server lets AI assistants like Claude for Desktop or Cursor query the FPL API through natural language commands, turning a simple chat into an interactive data exploration session.

For developers building AI‑powered sports applications, this server is invaluable because it abstracts away the intricacies of the FPL API. The MCP interface presents a clean, declarative contract: each tool receives structured arguments and returns JSON payloads that can be rendered or further processed by the assistant. This makes it trivial to embed dynamic league insights into chatbots, dashboards, or automated analysis pipelines without writing boilerplate code. The server’s design also ensures that the data remains fresh; it fetches current gameweek statistics on demand, so users always receive the latest points totals and transfer values.

Key capabilities include:

• Rich Player Data – Full statistics for every FPL player, such as points, form, and projected value.
• Team Information – Details about Premier League clubs, including squad lists and manager information.
• Gameweek Data – Current and historical gameweek summaries, enabling trend analysis across seasons.
• Player Search & Filtering – Find players by name, position, or team with fuzzy matching and pagination.
• Player Comparison – Side‑by‑side metrics for any two players, useful for transfer decisions or fantasy squad building.

Typical use cases span both hobbyist and professional domains. A casual fan might ask, “Show me the top 5 forwards by points this season,” while a fantasy manager could request a detailed comparison of two players over the last five gameweeks to decide on a transfer. In a research setting, data scientists could integrate the server into an AI workflow that automatically pulls player metrics, runs predictive models, and presents findings in a conversational interface.

Integration is straightforward for MCP‑compatible clients. Once the server is running, an assistant’s configuration simply points to its command or module path. The client then presents the available tools via a hammer icon, allowing users to invoke them with natural language. The server handles argument parsing and API communication transparently, returning structured results that the assistant can format or pass to downstream services. This seamless flow turns static data into an interactive, AI‑driven experience.

What sets the Fantasy Premier League MCP Server apart is its focus on a niche yet highly popular domain, combined with an open‑source, lightweight implementation that runs locally. Developers benefit from zero external dependencies beyond the standard FPL API, and the server’s modular design means it can be extended with additional tools—such as advanced statistical visualizations or predictive analytics—without disrupting existing workflows.