Why MapleBridge Open Uses an A2A Framing
MapleBridge Open uses an A2A framing because bilateral B2B matching is not just a single assistant filling a form. It is a coordination problem between a buyer-side agent, a seller-side agent, and a shared match and review layer.
What A2A Means Here
In MapleBridge Open, A2A means agent-to-agent workflow, not a public claim that the live marketplace is fully autonomous. The buyer-side agent and seller-side agent each manage a different domain model, then exchange normalized state through a shared match engine.
- The buyer agent structures demand, constraints, fit filters, and missing clarifications.
- The seller agent structures capabilities, capacity, compliance signals, and fulfillment boundaries.
- The match layer scores fit, confidence, and review priority across both sides.
- The notification layer decides when to request more data, when to suggest a match, and when to hand off to human review.
Why This Matters for B2B Matching
Most B2B tools still flatten everything into one CRM, one directory, or one lead form. That misses the fact that buyers and suppliers are not symmetric records. They expose different state, different risk, and different missing information. The A2A framing makes that boundary explicit.
- Buyer-side uncertainty is usually around specs, MOQ, packaging, certifications, timelines, and geography.
- Seller-side uncertainty is usually around process capability, export readiness, category fit, trust, and responsiveness.
- A shared match engine can only work well if both sides publish normalized but different contract surfaces.
What This Does Not Claim
The A2A label here does not mean MapleBridge Open exposes the live production app or production orchestration. It does not mean the marketplace runs without review, or that the public repo contains real crawler seeds, private prompts, or production scoring thresholds.
- The public repo publishes interfaces, not the production app.
- The public repo defines contracts, not live buyer and supplier data.
- The public repo explains scoring dimensions, not the private ranking weights used in production.