Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@RallyIQ remote MCP server Give me a game plan for Sinner against Alcaraz on clay."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Ask an AI assistant how a tennis player should play an opponent and get an answer from shot-by-shot match data instead of memory: where to serve on each court, which returns work against that server, which rally patterns to favour and avoid, who is likely to win, and why a match turned.
This repository holds:
the connection details for the RallyIQ remote MCP server at https://bigballi.com/RallyIQ/mcp,
a Claude plugin that adds that server plus a tennis-scouting skill, which teaches Claude how to read the numbers.
The server is run by RallyIQ, which models more than 11,000 ATP and WTA matches charted shot by shot by volunteers for the Match Charting Project. Each shot is valued by how much it changed its hitter's chance of winning the point. How it works: method.
"Give me a game plan for Sinner against Alcaraz on clay."
"Where does Iga Swiatek serve on break points, and is her serve easy to read?"
"What are Coco Gauff's biggest weaknesses, and who is best equipped to exploit them?"
"Why did Djokovic lose the 2023 Wimbledon final?"
"Which active WTA players choose their shot direction best?"
Related MCP server: livetennisapi-mcp
All tools are read-only (readOnlyHint: true) and need no account.
Tool | What it answers |
| One player against an opponent, optionally on one surface: the match forecast with a 90% range, first-serve directions and the optimal mix on each court against that returner, the opponent's serve, the best returns against that server, rally shots to favour and avoid, career shot ratings side by side and the charted head-to-heads. |
| One player's scouting report: serve and return points won against an average opponent, shot ratings per 100 shots with tour percentiles, first-serve habits including on break points, how exploitable the serve is, the shots they hurt opponents with and the shots they are most exposed to, and similar players. |
| Why a charted match went the way it did: each player's points against expectation split into direction choice, shot selection and execution, by stroke and by set, and the points each left on the table. |
| The top 10 ATP or WTA players on one of ten tactical measures, active or across eras. |
Every value comes with a 90% margin and a link to the full page on RallyIQ.
Settings → Connectors → Add custom connector, then paste https://bigballi.com/RallyIQ/mcp. No sign-in is needed.
Install the plugin, which adds the server and the tennis-scouting skill:
/plugin marketplace add BigBalli/rallyiq-mcp
/plugin install rallyiq@rallyiqOr add only the server:
claude mcp add --transport http rallyiq https://bigballi.com/RallyIQ/mcpAny client that supports remote MCP servers over Streamable HTTP can use https://bigballi.com/RallyIQ/mcp with no credentials. The server speaks protocol versions 2026-07-28, 2025-11-25, 2025-06-18 and 2025-03-26 and answers with JSON (no SSE, no sessions).
The server receives the tool name and its arguments (for example two player names and a surface), uses them to answer, and does not store them. It never sees your conversation or your account. Full policy: bigballi.com/RallyIQ/privacy.
Email g@bigballi.com, or see bigballi.com/RallyIQ/connect.
The contents of this repository are released under the MIT License. The data served by the RallyIQ MCP server is not part of this repository: it derives from the Match Charting Project and is licensed CC BY-NC-SA 4.0, which requires crediting the Match Charting Project wherever it is used.
This server cannot be deployed
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