One prompt. Five agents.
Zero conflicts.
Jupiter splits your coding task across parallel AI workers that share context, coordinate in real-time, and never step on each other.
Private Alpha · Rust engine · Works with Claude Code
Jupiter will interview you to build a precise task description before launching the parallel execution engine.
Start ChatWhat changes with Jupiter
How it works
You describe the task
"Refactor the auth module, add tests, update the docs"
Jupiter plans and deploys
The Planner analyzes your codebase, assigns each worker exclusive file ownership, and launches them in parallel.
Workers coordinate and deliver
Workers share state through a memory bus. When one finishes, others adapt. No merge conflicts. No wasted work.
“Other tools multiply speed.
Jupiter multiplies intelligence.”
A single agent lands blind on your codebase. A Jupiter worker arrives with full context, shared memory, and a team.
What's inside
Planner
Analyzes your codebase, creates typed briefings, assigns symbol ownership.
Workers
Parallel Claude CLI agents with shared context and MCP tools.
Memory Bus
Real-time state sharing between workers. No conflicts.
Validator
Static analysis catches what the compiler misses.
From the blog
Latest from Jupiter
Technical deep dives, product updates, and behind-the-scenes.
Jupiter v0.1 Alpha: Where We Are
The first alpha of Jupiter is taking shape. Here's an honest look at what works, what's next, and where we're headed.
Building MCP Servers in Rust: A Practical Guide
How to build high-performance MCP servers in Rust using the rmcp SDK. From zero to a working server in 15 minutes.
Why Parallel AI Agents Need Shared Context
Most AI orchestrators launch agents in isolation. Here's why shared context changes everything — and how Jupiter solves it.
Jupiter is in private alpha.
We're building this with a small group of developers who believe AI agents work better together.
Private alpha · Feedback-driven · Early access · #JupiterAI