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Alternatives

Products that do what PromptChess does

Chess.com for AI agents

  1. 1

    Transform Your Chess Skills with AI-Powered Training

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  2. 2

    AI Agents without nodes headaches

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  3. 3IB

    Hi! I build an MCP server that allows clients to play Minesweeper. It turns out that Claude is not very good at it (makes obvious mistakes, hasn't won a single game on a 9x9 board after many attempts). I am curious how I can prompt Claude to do better?

    2025 · github.com

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    agent.ai586

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    muno104

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    Pensieve133

    Full company context for every AI agent

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  9. 9MM

    I built a March Madness bracket challenge for AI agents, not humans. The human prompts their agent with the URL, and the agent reads the API docs, registers itself, picks all 63 games, and submits a bracket autonomously. A leaderboard tracks which AI picks the best bracket through the tournament. The interesting design problem was building for an agent-first user. I came up with a solution where Agents who hit the homepage receive plain-text API instructions and Humans get the normal visual site. Early on I found most agents were trying to use Playwright to browse the site instead of just…

    Mar 2026 · bracketmadness.ai

  10. 10

    The fastest way to connect your data with your AI Tools.

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  11. 11

    Chess for macOS

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    deduce66

    A daily Wordle-like puzzle for AI agents

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  13. 13

    ​​The agentic AI ecosystem, in one directory​

    1d ago · aiagentslisting.com

  14. 14
    AutoMCP150

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    Task management for the age of agents

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    Build and control voice AI agents via MCP

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  17. 17

    The memory layer for AI agents

    Jul 2026 · kitforai.com

  18. 18BA

    Sep 2025 · thealliance.ai

  19. 19IT

    I built 1e4.ai - a chess web app where you play against neural networks trained to mimic human Lichess players at specific Elo ranges. There's a separate model for each 100-point rating bucket from ~800 to 2200+, and the bots not only choose human-like moves but also burn clock time, play worse under time pressure, and blunder in human-like ways. Live demo: https://1e4.ai Code: https://github.com/thomasj02/1e4_ai A few things that might be interesting: - Trained on almost a full year of Lichess blitz games, around 1B total games - Architecture is an a small…

    May 2026

  20. 20AB

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  21. 21

    Send your AI agent to an LLM prompt-injection arena

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  22. 22

    An AI chess coach that analyzes your own games

    Jun 2026 · chesscoach-web.vercel.app

  23. 23NT

    Today we're releasing Nanobot an open-source framework for building AI agents on top of the Model Context Protocol (MCP). MCP servers are a great way to expose structured tools, but they’re usually just that—collections of functions. Nanobot makes it simple to wrap any MCP server with reasoning, a system prompt, and orchestration so it behaves like a real agent. Even better, Nanobot fully supports MCP-UI, so agents can pass rich interactive components (forms, dashboards, even mini-apps) directly into chat. A simple example: if you had a Blackjack MCP server with tools like deal, bet, and…

    Sep 2025 · nanobot.ai

  24. 24
    Utter14

    Plan the work. Ship it with your AI agents.

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