OP.GG MCP Server

The OP.GG MCP Server bridges the gap between popular esports and competitive game data and AI assistants that rely on the Model Context Protocol. By exposing a rich set of tools for League of Legends, Teamfight Tactics, Valorant and esports scheduling, the server allows developers to query live statistics, meta trends, and player performance without leaving their AI workflow. This eliminates the need to build custom scrapers or maintain separate APIs, giving agents instant, reliable access to up‑to‑date information that would otherwise require manual aggregation.

At its core, the server provides a collection of function‑calling endpoints that return structured JSON payloads. For example, the lol-champion-analysis tool delivers counter‑data and ban/pick statistics, while tft-meta-trend-deck-list surfaces the current meta decks for Teamfight Tactics. Each tool is carefully documented with required parameters and response schemas, enabling developers to compose complex queries—such as “find the best champion for a given role and meta” or “retrieve a player’s recent Valorant match history”—directly within an AI assistant conversation. The consistent interface means that any MCP‑compatible client can tap into the same data set, fostering interoperability across platforms.

Key capabilities include real‑time leaderboard retrieval (lol-champion-leader-board, valorant-leaderboard), historical game data for individual summoners or players (lol-summoner-game-history, valorant-player-match-history), and meta‑driven insights such as champion item builds (tft-champion-item-build) or map composition analysis (valorant-agents-composition-with-map). The esports tools add a layer of scheduled match information and league standings, which can be leveraged for event prediction or betting analytics. Because the data is served over HTTP and conforms to MCP standards, agents can seamlessly integrate these calls into broader reasoning chains or knowledge‑graph queries.

Real‑world scenarios abound: a game‑analysis bot can answer questions like “Which champions are currently underperforming on the top lane?”; a coaching assistant can recommend optimal item builds for a TFT champion based on current meta trends; or an esports commentator’s AI companion can pull live schedule updates and team standings to enrich commentary streams. Developers building dashboards, chatbots, or automated analytics pipelines can simply reference the appropriate MCP tool without wrestling with API keys or rate limits.

What sets OP.GG apart is its breadth of game coverage coupled with a unified, machine‑friendly interface. By centralizing diverse data sources under one MCP server, it removes friction from integrating competitive gaming analytics into AI workflows. Whether you’re building a player‑support assistant, an automated scouting tool, or a real‑time commentary helper, the OP.GG MCP Server delivers accurate, actionable data that keeps your AI agents informed and engaging.