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Molecule AI vs AutoGen — when each one fits
AutoGen is a multi-agent conversation framework. Molecule AI is a control plane. AutoGen's GroupChat lives within one Python or .NET application; Molecule AI's workspace tree spans processes and machines and is auditable from a canvas. You can use both by operating AutoGen yourself and connecting a custom adapter through Molecule's external registration mode. The adapter keeps its own safe RuntimeId; AutoGen is not in official runtime discovery.
What each tool does
AutoGen is an open-source framework built by Microsoft for orchestrating conversations between agents. The core abstraction is the ConversableAgent — an agent that can send and receive messages — and the GroupChat / GroupChatManager that coordinates several ConversableAgents around a shared conversation. It is documented at microsoft.github.io/autogen; we link out rather than paraphrase so anything we say here can be checked against the canonical source.
Molecule AI is the open-core control plane for heterogeneous AI agent teams. It introduces platform-level primitives that no agent SDK ships on its own: every agent has a workspace identity with private and shared hierarchical memory, workspaces delegate over A2A across processes and machines, and the topology is editable on the canvas. Managed runtimes come from the SDK contract; other frameworks connect as external agents.
Side-by-side
Layer-by-layer. Where AutoGen ships a capability we note it explicitly; where the capability belongs to the layer above, we point to that layer instead of asserting AutoGen lacks it.
| Layer | AutoGen | Molecule AI |
|---|---|---|
| Single agent + tool use | Yes — ConversableAgent | — (delegated to SDK) |
| In-process multi-agent conversation | Yes — GroupChat + GroupChatManager | One GroupChat = one workspace; many workspaces compose into a tree |
| Cross-process / cross-SDK orchestration | — (one Python/.NET application) | Across workspaces, runtimes, processes, machines |
| A2A delegation protocol | — | JSON-RPC 2.0 with audit + HITL gates |
| Hierarchical memory (LOCAL/TEAM/GLOBAL) | — | Built-in (HMA) |
| Cross-SDK interoperability | — (single SDK) | Claude Code, Codex, Hermes, OpenClaw managed; external agents supported |
| Visual topology editor | — (GroupChat is code) | Canvas (drag workspaces, draw delegations) |
| License | MIT (per microsoft/autogen repo) | BSL 1.1 (self-host freely; restricts commercial resale as a competing hosted service) |
| Hosted offering | Self-host (AutoGen is library-first) | $29 per workspace per month (Team plan) |
When AutoGen alone is the right answer
If your multi-agent system is a conversational team that fits inside one Python (or .NET) application — a researcher agent talking to a coder agent talking to a critic agent, all sharing context through a single GroupChat — AutoGen by itself is a great fit. The conversation is the centerpiece of the framework; that is exactly what you want. Adding a control plane on top would not earn its weight while everything fits in one process.
When you'd want Molecule AI on top
If you have multiple services that need to coordinate, need delegation that is audited and approval-gated, or want non-engineers to read and steer the topology from a visual canvas, that is what Molecule AI adds. A self-operated AutoGen service can participate as an external agent alongside managed workspaces.
Can I use both?
Yes. Operate the AutoGen service yourself and connect a custom adapter through external registration. The adapter retains its safe RuntimeId, and Molecule manages the workspace and collaboration boundary without claiming AutoGen as an official runtime.
References
We cite every cross-project claim against the project's own canonical source rather than paraphrasing. If a claim on this page disagrees with the linked source, the linked source is right — open an issue and we'll fix the page.
- AutoGen documentation: microsoft.github.io/autogen
- AutoGen repository (MIT license): github.com/microsoft/autogen
- Molecule AI architecture: moleculesai.app/architecture
- Molecule AI glossary: moleculesai.app/glossary
- Molecule AI pricing: moleculesai.app/pricing
Frequently asked questions
Is AutoGen the same as Molecule AI?
AutoGen is a multi-agent conversation framework; Molecule AI is a control plane. AutoGen coordinates agents inside an application. Molecule AI provides workspace identities, A2A delegation, hierarchical memory, and a visual canvas across agents. They cover different layers.
When should I use AutoGen without Molecule AI?
If your multi-agent system is a conversational team that fits inside one Python or .NET application, AutoGen by itself is a great fit. The conversation is the centerpiece of the framework — that is exactly what you want. Adding a control plane on top would not earn its weight while everything fits in one process.
Can an AutoGen GroupChat connect to Molecule AI?
Yes, through a custom adapter and the external registration mode. The adapter retains its own safe RuntimeId. AutoGen is not an official runtime, so Molecule does not provision or operate it as a managed workspace image.
Compare with other tools
Comparison pages explain product layers; the comparison index does not define managed runtime support.
Comparison policy: this page positions Molecule AI against AutoGen as honestly as we can. We do not assert performance advantages, we do not benchmark, and we deliberately link to AutoGen's own documentation for every AutoGen claim. If Microsoft would like a change, contact hello@moleculesai.app and we will revise.