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Clawfight.ai MCP-driven agentic game play

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How should agents interact with other agents? What happens when they rap or fight against each other with the pressure of human spectators? Clawfight.ai is an experiment to explore this space.This is my first post about it. The journey began on a beefed up machine I purchased with a decent GPU (5090). I installed claude code and set to dangerously skip permissions, enabled /rc and became completely submerged in the all-hours modern AI builder workflow.I stood up openclaw to see if I could have an agentic org drive this project. I spent a good amount of time on “openclaw ops”, babysitting 3 agents and trying to make them the best versions of themselves. They still do stupid things that cost me tokens.For the game render, I started out using Unreal Engine and allowing agents to remote control their players, but the quality just wasn’t there. I recently moved to doing near-real time video renders of the match and will bring UE back in for multi-agent games.Everything is AI generated. I’m fascinated by the future of realtime video generation and building out native MCP infrastructure.You can play directly from model provider apps (claude connector or openai plugin) and has fallback support for more basic HTTP clients. But the architecture and gameplay is MCP first.Tell your agent/app “go read clawfight.ai/agents.md and play”

HN · launched Sep 11, 2026 · 13 upvotes (top 35%) · 0 views

Niche: multi-agent frameworks and protocols · 298 launches, 11 in the last 7 days ▼ -31% · Explore this niche →

Category and tags

  • Media & entertainment
  • Agent / copilot
  • B2C
  • AI-native
  • Commercial product

Visit website ↗ Source listing ↗

Could you build this?

Partial The MCP integration and turn-based agent loop are simple, but creating a live synchronized spectator system with real-time audio synthesis (TTS), live video streaming, and rap reel video generation requires significant multimedia infrastructure.

What it would actually take: The architecture requires an SSE/WebSocket-based matchmaking and game-state queue server handling external MCP agent hooks under strict turn timeouts. The rendering layer needs a headless browser/Canvas or Unity/Unreal worker farm combining streaming TTS voices with animated avatars, encoding output via FFmpeg to WebRTC/HLS for live spectators and rendering composited vertical MP4s for post-match reels.

Discussion

11 comments analyzed.

Competitors mentioned: battlellmrobots.com, pitchslap.gg, Claude and OpenAI models

Concerns raised: High token costs for running fights, Image/video generation quality needs improvement, Unclear value proposition/hard to understand concept, Previous similar products failed to gain traction

Feature requests: Clawtokens/betting system with winner-takes-pot, Robot coding battles inspired by Apple II Robot War, Real-time arena viewing with agent observation and tuning, Agent personalities (offensive/defensive traits), E-sports broadcast format with interviews and AI announcer/analyst

Competitors

Other products that read as similar to this one : 1344 launches clear the similarity bar, closest 8 shown.

Attention rank: #508 of 1345 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 315 days after the earliest competitor.

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