Agent Squad
Lightweight open-source multi-agent orchestration framework: a classifier routes each user query to the most suitable specialized agent while conversation context is maintained across agents; a SupervisorAgent adds team coordination via an agent-as-tools architecture.
Description
Agent Squad (formerly multi-agent-orchestrator, previously hosted at awslabs/agent-squad, now maintained at 2fastlabs/agent-squad) orchestrates multiple specialized agents behind a single conversational surface. Every user turn is analyzed by a Classifier that uses agent descriptions plus conversation history to select the best agent; the Orchestrator dispatches the turn, saves the exchange, and returns the response. A built-in SupervisorAgent implements an agent-as-tools architecture in which team members are exposed to a supervisor as invocable tools, enabling parallel processing and contextual communication. Python and TypeScript runtimes maintain feature parity and run anywhere from AWS Lambda to a laptop; a Swift runtime brings the same orchestration model — classifier routing, native and MCP tools, realtime voice, tracing — fully on device for Apple platforms.
Solution
User input -> Classifier (agent descriptions + history) -> selected agent processes the turn -> Orchestrator saves the exchange and returns the response; optionally a SupervisorAgent fans work out to team agents exposed as tools and aggregates their results.
Primary use cases
- routing one conversational surface across many specialized agents
- supervisor-coordinated agent teams
- serverless and on-device multi-agent deployment
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