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// comparison

open-multi-agent vs Semantic Kernel

Semantic Kernel is Microsoft’s enterprise LLM SDK for .NET, Python, and Java; open-multi-agent is a TypeScript-native task-DAG runtime. Microsoft is now converging its agent work into the Microsoft Agent Framework.

Enterprise support
Pick Semantic Kernel if

You’re in the Microsoft / .NET / Azure ecosystem and want a first-party SDK; plugins, functions, agents; with a supported path forward via the Microsoft Agent Framework.

Pick open-multi-agent if

You’re in Node/TypeScript and want a lean, provider-neutral, goal-driven runtime with three dependencies and a run-level token circuit breaker; no .NET, no Azure assumption.

Heads-up: in 2026 Microsoft began converging Semantic Kernel and AutoGen into the new Microsoft Agent Framework (Python + .NET) as the go-forward multi-agent stack. Semantic Kernel remains supported, but if you’re choosing for a new, long-lived project, weigh building on the Agent Framework directly.
01 at a glance

Side by side.

Dimensionopen-multi-agentSemantic Kernel
Language / runtimeTypeScript-native; embeds in any Node.js 20+ backend.NET / C#-first; first-party Python and Java; no TypeScript
Orchestration modelOne agent, an explicit task DAG, or a goal the coordinator decomposes at runtime; explicit mode, governance policy, or an ExecutionRouter selects the topology, and a run can revise its not-yet-executed tasksPlugins / functions plus agents; multi-agent orchestration is moving to the Microsoft Agent Framework
Runtime dependencies3 direct (Anthropic SDK, OpenAI SDK, Zod); extra providers and MCP are opt-in peers~22 direct in the Python package; the newer Agent Framework core is much leaner (~4)
Mixed-model teamsYes; each agent runs its own cloud or local model in one team; model routing can send planning to a flagship model and leaves to a cheap oneYes; per-agent model / service
Run-budget controlRun-level token and estimated-USD ceilings — maxTokenBudget, or maxCostBudget with your estimateCost table — checked between model calls and task dispatches; one in-flight model turn can cross the ceilingNo hard token cap
ObservabilityTraceRecord v2 + TraceStore, stable run identity, an optional first-party OTel adapter, and an offline post-run Run Viewer — no hosted service requiredNative OpenTelemetry
02 actual capabilities

What open-multi-agent includes.

OMA is more than goal decomposition and a small dependency count. These are current framework capabilities documented in the project README.

Dynamic, explicit, and routed orchestration

runTeam() builds a task DAG from a goal, runTasks() runs a graph you define, and runAgent() covers one agent. Explicit mode, governance declarations, or a custom ExecutionRouter choose Single or Team execution and expose a routingDecision. Opt-in hybrid routing adds one semantic assessment where the deterministic result would be Single — the policy that decides stays deterministic. Plans remain previewable, reviewable, and replayable as data.

Governance and approvals at distinct boundaries

Declare required or preferred roles, ordered review paths, and budget-aware degradation. Gate the plan with onPlanReady, one ready task with onTaskDispatch, one consequential tool call with onToolCall, and any mid-run plan revision with onPlanPatch; then inspect governanceConclusion.

Event-driven scheduling and task evidence

Ready dependents start as soon as prerequisites complete. Hard task requirements are enforced across every assignment strategy, so an unsatisfiable task is rejected instead of dispatched to an ineligible agent; taskResults preserves unmerged task outputs and structured dependency payloads carry bounded provenance. Retries and checkpoints resume from completed task boundaries, and opt-in repairable recovery can append replacement work at an outcome barrier before any original dependent starts.

Production controls

Bound each run with turn, token, estimated-cost, timeout, context, and loop limits. maxTokenBudget and maxCostBudget stop further calls after a boundary check; one in-flight model turn can cross the ceiling. Model routes support ordered fallbacks. Built-in tools are default-deny, and trace payloads redact detected secrets on a best-effort basis.

Your environment and your models

Run in your own Node.js backend — locally, offline, or air-gapped, on your own credentials, with no hosted service. Mix cloud and local models in one team, connect MCP tools, and bring external agents in through ACP or process backends.

Inspect, trace, and evaluate

Stable run identity, routing decisions, privacy-preserving execution receipts, TraceStore, and the offline Run Viewer work with no hosted service. Score quality with versioned EvalSets and GateVerdict, including a routing-stability gate, then connect runs to production telemetry through the optional OTel adapter.

03 mechanism

How they differ.

Semantic Kernel provides plugins, functions, planners, and agents. It is built C#-first with first-party Python and Java support, and integrates with Microsoft and Azure services. Its multi-agent direction is the Microsoft Agent Framework, which unifies SK and AutoGen. open-multi-agent is a TypeScript-native runtime that decomposes a goal into a task DAG at runtime, assumes no particular cloud, and carries three direct dependencies.

Where Semantic Kernel fits

Semantic Kernel or the Microsoft Agent Framework fits .NET and Azure projects that require Microsoft-supported SDKs, Azure integrations, and native OpenTelemetry.

Semantic Kernel on GitHub

Where open-multi-agent fits

open-multi-agent fits when your stack is Node/TypeScript and you want to stay there: a lean, provider-neutral, goal-driven runtime with three dependencies and a boundary-checked maxTokenBudget circuit breaker, with no .NET runtime or Azure assumption. The coordinator plans the task DAG from a goal instead of you assembling plugins and planners.

Quick Start
// Enterprise

Taking this to production?

open-multi-agent is MIT-licensed and free to run yourself. When you need it delivered, integrated, or supported on a deadline, 元定义科技 (YuanASI) offers commercial delivery and support.

Enterprise support