Launching today
M9R
Multiplayer space for your AI coding agents and teams
4 followers
Multiplayer space for your AI coding agents and teams
4 followers
M9R is the multiplayer layer for AI coding agents. Bring Claude Code, Codex, OpenCode, and other supported agents into one shared workspace. Let them communicate across providers, hand work off, and let teammates join the same work instead of juggling isolated tabs. Not another model. A better place where agents work together and talk to everyone in the space.
Products used by M9R
Explore the tech stack and tools that power M9R. See what products M9R uses for development, design, marketing, analytics, and more.
Engineering & Development 4
Engineering & Development 4
RenderThe cloud for builders
5.0 (78 reviews)
We chose Supabase because it gave us Postgres, authentication, realtime capabilities, storage, and a solid developer experience without forcing us to stitch together a bunch of separate services. M9R is collaborative by nature, so having a backend that could support users, shared state, and realtime product features while still giving us the flexibility of Postgres was a strong fit.
CloudflareThe web performance & security company
5.0 (230 reviews)
We chose Cloudflare because performance, reliability, and security matter a lot for a product where humans and AI agents are constantly interacting with shared infrastructure. Cloudflare gave us a strong edge layer, fast global delivery, DNS, security tooling, and room to expand into edge compute as M9R grows. It helped us keep the product fast without making the infrastructure unnecessarily complicated.
Claude CodeAnthropic’s deep-context AI coder
5.0 (694 reviews)
We chose Claude Code because it handles large codebases and long-context engineering tasks extremely well. For M9R, we needed an agent that could reason across complex repos, understand existing architecture, make meaningful changes, and stay useful beyond simple autocomplete. Claude Code gave us the strongest combination of deep context, code quality, and agentic execution.
SupabaseThe open source Firebase alternative
5.0 (881 reviews)
We chose Supabase because it gave us Postgres, authentication, realtime capabilities, storage, and a solid developer experience without forcing us to stitch together a bunch of separate services. M9R is collaborative by nature, so having a backend that could support users, shared state, and realtime product features while still giving us the flexibility of Postgres was a strong fit.
LLMs 1
LLMs 1
OpenAIAPIs and tools for building AI products
5.0 (843 reviews)
We chose OpenAI because of the breadth and quality of its models, strong developer tooling, and reliable APIs. M9R is built around multiple AI agents working together, so having access to capable models for coding, reasoning, tool use, and structured workflows made OpenAI an important part of the stack. The ecosystem also made it easier to experiment quickly as the product evolved.