Overview

The TFT MCP Server is a dedicated Model Context Protocol service that bridges AI assistants with live Team Fight Tactics (TFT) game data. By exposing Riot Games’ TFT APIs through a lightweight MCP interface, it allows Claude or other AI assistants to retrieve match histories and detailed game analytics on demand. This eliminates the need for developers or content creators to manually query the Riot API, parse JSON responses, and maintain authentication keys, enabling a seamless integration of real‑time TFT data into conversational or analytical workflows.

The server offers two primary tools that cover the most common data retrieval needs for TFT players and analysts. The tool fetches a configurable list of recent matches for the authenticated summoner, supporting pagination via and parameters. The tool, on the other hand, pulls granular information about a single match given its . Together, these tools provide a complete view of a player’s recent performance and the underlying mechanics of each game. For developers, this means they can ask an AI assistant to “show me my last 10 games” or “give me the breakdown of match X”, and receive structured data ready for further processing or visualization.

Key capabilities include automatic handling of API key rotation, error propagation through MCP responses, and a straightforward configuration schema that plugs directly into Claude Desktop. The server runs over stdio, so it can be launched in any environment that supports Node.js 14+. Because the MCP SDK is used under the hood, developers can extend or customize the server with minimal effort—adding new tools for champion statistics, item builds, or even predictive modeling without touching the core protocol implementation.

Real‑world use cases are abundant. Competitive TFT coaches can feed match histories into an AI assistant to generate post‑match reports, while streamers can ask for on‑the‑fly insights into their audience’s gameplay. Data scientists building TFT analytics dashboards can embed the MCP server as a backend service, letting their models query live data through the same interface used by conversational agents. In research settings, the server facilitates reproducible experiments by providing a stable API surface that abstracts away authentication and rate‑limit concerns.

What sets this MCP server apart is its focus on TFT, a niche yet rapidly evolving game. By providing ready‑made tools for the most frequently requested data types, it saves developers hours of boilerplate code and reduces friction when integrating Riot’s APIs into AI‑powered applications. The result is a powerful, developer‑friendly bridge that unlocks real‑time TFT insights directly within the conversational context of modern AI assistants.