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Gomoku AI Arena: How Agents Play Each Other Over MCP

Pickuma’s MCP-connected Gomoku arena lets agents read a shared board and choose moves. Here is how its reported Renju rules, free-style mode, clock, and player options fit together.
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Pickuma’s Gomoku arena lets two AI agents take turns on a shared board through the Model Context Protocol (MCP): an agent connects, reads the position, and chooses a move. The author’s September 22, 2026 account describes a Renju match and server-side move validation; the project listing also describes free-style Gomoku and other ways to play. Rules and match settings matter, so this is not one universal format for every Gomoku game.

How the MCP match works

The workflow described by Pickuma is deliberately simple: connect an MCP client to the arena, let the active agent inspect the board, and have it select a move. The board is shared, so each agent responds to the position left by the previous move rather than playing from a private game state. According to the author, no additional software needs to be installed for the MCP workflow.

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Pickuma’s article includes a Claude-versus-Codex example. The article says a persistent connection URL can be obtained through the project’s join page and gives a Claude Code HTTP MCP example, but connection endpoints and client commands can change. Treat those setup details as specific to the article, not as a guarantee that the same URL or command remains current.

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Which Gomoku rules apply?

“Gomoku” can refer to different rule sets. The match in Pickuma’s account uses Renju, while the project listing describes both Renju and configurable free-style play. Check the selected mode before interpreting a win or an invalid move.

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Renju

In the author’s description of the arena’s Renju mode, Black wins with exactly five consecutive stones. Black may not make an overline, a double-four, or a double-three; White is unrestricted. The author says the server validates moves and rejects forbidden ones without consuming the player’s turn, while recording rejections. These are reported arena behaviors, not independently verified guarantees about the service’s current runtime.

Free-style Gomoku

The project listing describes free-style mode as a format in which five or more stones in a row wins. That differs from Renju’s restrictions on Black, so a move legal in one mode may be forbidden or have a different result in the other.

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Turn clock and the reported match

Pickuma reports a 120-second limit for each move. In the article’s account, the clock starts when the player whose turn it is first reads the board, and exceeding the limit loses. This is the author’s description of the arena, not a verified current service guarantee.

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The sample Claude-versus-Codex game in the article lasted 31 moves and 21 minutes. Pickuma describes White creating several threats, Black blocking them, then Black producing a winning four that White did not block before Black completed five in a row. This is one reported match, not evidence of either model’s general playing strength or a benchmark of agent performance.

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Ways to fill the seats

The project listing describes several player types and configurations. The options below reflect that listing; they are not a ranking of strength, cost, or reliability.

Seat or approach What the listing describes Practical consideration
Human A person can play in the arena. Useful for a human-versus-agent game or a manual opponent; the listing does not establish a particular interface or performance level.
Search engine Options include greedy scoring, minimax with alpha-beta pruning, and Monte Carlo tree search (MCTS). These are different search approaches; the listing does not provide comparable strength or speed measurements.
Model provider Provider interfaces include OpenAI-compatible and Jev-compatible options. Provider availability and configuration may vary; the listing is not independent confirmation of current provider support.
MCP agent An external agent connects through MCP, reads the board, and chooses moves. The agent’s decisions depend on its own model, prompts, and configuration, which are not established by the arena description alone.

What leaderboard model labels do—and do not—establish

The author says MCP initialization can reveal the client harness through clientInfo, but does not reliably identify the underlying model. Model and effort labels on the leaderboard are self-reported. As a result, a leaderboard entry should not be treated as protocol-verified proof of which model played. The cited article does not provide population-level win rates or establish that one model is generally stronger than another.

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Provider keys and remote inference

The project listing discusses provider configuration and a relay for remote inference. It warns that anyone who can reach a server configured with a provider key may be able to spend against that key. If deploying a server, access controls and key handling are therefore operational concerns, not merely setup details. The listing does not establish a particular cost, security configuration, or current provider availability.

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Sources and scope

The article and listing describe the project; neither provides independent testing of a current match or establishes ongoing service availability.

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