Overview¶
MAS-Lab is for developers, enterprises, and researchers who need multi-agent systems that remain understandable as they grow. This page expands on the home introduction for each audience.
For developers¶
Build modular multi-agent applications using explicit specifications instead of hidden prompt and code glue.
Declare agents, tools, workflows, and contracts once, then iterate safely across models, tools, and coordination patterns. The runtime enforces contracts at important boundaries — tool calls, delegations, model requests — so changes do not propagate unpredictably through the whole stack.
Use the design-space labs to compare coordination patterns and topologies before production. Start with Tutorial 0.
For enterprises¶
Deploy agentic systems with governance, traceability, and operational control built in.
MAS-Lab separates business intent, runtime execution, observability, and policy enforcement. Governance policies — budgets, approvals, delegation rules, tool access — are expressed as overlays rather than buried in application code.
See the user guide for install, configuration, and day-to-day workflows.
For researchers¶
Run controlled, reproducible experiments on multi-agent systems.
Experiments tie to an explicit specification, so observed differences are more likely to reflect the variable you changed — not hidden stack drift. Multi-run campaigns, overlays, and integrated observability support rigorous comparison of agent designs, coordination patterns, and governance mechanisms.
Reproduce the article's Section 5 evaluations via paper labs.
The problem in brief¶
Prototype multi-agent demos are easy; production-grade trust is not. When logic, orchestration, and control are interwoven, teams struggle to reproduce behavior, attribute failures, or evolve systems safely.
MAS-Lab's response is a specification-driven foundation: intent, execution, observability, experimentation, and governance share one model — from the first lab run through deployment. See the home page for a short introduction.