For AI-Native Development
The Multi-Agent
Communication Protocol
For AI-native development workflows with orchestrated parallel agents, each needs to know what the others are doing—without inheriting their full context. Stage lets agents stay in their lane while staying aware.
Feature flags let teams ship without coordinating deploys.
Stage lets agents build without coordinating context.
4 agents. 1 truth. Parallel progress.
Multiple actors
share the Stage.
Every token spent re-explaining shared assumptions is a token not spent solving problems. Stage externalizes the world model so agents can focus on the work.
The Problem with Parallel Agents
Modern AI development isn't one agent, one conversation. It's:
- A frontend agent building UI
- A backend agent implementing APIs
- An infra agent configuring deployments
- A QA agent writing tests
Each agent has a context window. Each context window is precious.
- → Re-explaining assumptions causes compaction
- → Duplicating context causes drift
- → Sharing chat logs doesn't scale
Agents don't share chat logs.
They need to share contracts.
Orchestrator Awareness
Parallel agents see what others have claimed and built—without copying their conversations. Stay in your lane. Stay aware.
Context Optimization
Stop burning tokens re-explaining shared assumptions. Agents read contracts from Stage. Context windows stay lean and focused on the task.
Shared World Model
The contract is the spec. The spec is the truth. One source of assumptions that every agent can read, none have to carry.
Claude thinks. Stage remembers.
The LLM is the interface. Stage is the infrastructure.
Three steps to agent coordination.
Stage sits between your agents and their shared understanding. Agents write contracts. Other agents read them. The orchestrator stays lean. Everyone builds against the same truth.
Connect
Point your agents at Stage. One SDK call or environment variable. Contracts flow through Stage—agents stay in sync.
import { Stage } from '@usestage/sdk';
const stage = new Stage({ project: 'my-app' });Stage Contracts
Agents write the contracts they need. Other agents read them as specs. The contract becomes the source of truth.
// Frontend agent stages what it needs
stage.contract('users-api', {
endpoint: '/api/v2/users',
returns: { id: 'string', name: 'string' }
});Coordinate
Agents discover contracts, build against them, and ship. No prompt copying. No context duplication. Just shared truth.
// Backend agent reads the contract
const spec = await stage.read('users-api');
// Implements to spec...Built for how AI actually works.
Stage solves the coordination problems that emerge when multiple agents build software in parallel. No more prompt copying. No more context bloat. No more agents working against each other.
Parallel Agent Development
The Problem
Your orchestrator spawns a frontend agent and a backend agent in parallel. The frontend needs to build against an API that doesn't exist yet. The backend doesn't know what shape the frontend expects. Both waste tokens asking each other questions through the orchestrator.
With Stage
The frontend agent stages the contract it needs. The backend agent reads that contract as its spec. Both build against the same truth. Zero coordination overhead. Zero context duplication. The contract is the conversation they never had to have.
Toggle to see the difference
Why not just copy prompts?
You could relay context through the orchestrator. You could inject shared assumptions into every prompt. But that doesn't scale.
Stage does.
| Challenge | Without Stage | With Stage |
|---|---|---|
| Where do shared assumptions live? | Copied into every agent's context | Externalized to Stage |
| How do agents learn about changes? | Re-explained by orchestrator | Read from Stage directly |
| What happens at context compaction? | Assumptions get summarized away | Contracts persist in Stage |
| How do new agents get context? | Massive prompt injection | Point them at Stage |
| Can agents build against futures? | Only what exists today | Stage any contract shape |
| Orchestrator overhead? | High—constant relay | Low—just coordinates |
Not another prompt template
Prompts are ephemeral. They get summarized, truncated, forgotten. Stage contracts persist outside the conversation. They survive context compaction. They outlive the agent that created them.
Not a shared document
Docs require agents to read, parse, and carry in context. Stage is queryable infrastructure. Agents fetch exactly what they need, when they need it. No context bloat.
Not a database
Databases store data. Stage stores contracts—typed, versioned, discoverable specifications that agents can build against. It's the difference between storing facts and storing agreements.
Built for agent coordination
Stage is purpose-built for the multi-agent world. Contracts are first-class. Discovery is built in. Versioning is automatic. It's what MCP would be if it were designed for parallel agent development.
Without Stage
O(n²) coordination overhead
With Stage
Contracts are the coordination
Start coordinating. Start free.
No credit card required. Scale as your agent swarm grows.
Free
For developers exploring AI-native workflows
- 10,000 contract reads/month
- 25 staged contracts
- 3 agent connections
- Community support
- 7-day contract history
Pro
For teams building with parallel agents
- 500,000 contract reads/month
- Unlimited contracts
- Unlimited agent connections
- Email support
- SSO / SAML
- 90-day contract history
- Contract versioning
Enterprise
For organizations scaling AI development
- Unlimited everything
- Dedicated infrastructure
- Custom agent SDKs
- Dedicated support
- SLA guarantee
- On-prem deployment
- Audit logs
- Advanced security controls
Questions? Check our FAQ or contact us.
Your agents are ready.
Give them Stage.
Stop burning tokens on coordination. Stop copying context between agents. Stop watching orchestrators struggle with relay overhead. Stage gives your agents the shared truth they need to build in parallel.
contracts → coordination → shipped