Comparison Preset
Neither framework is a clear choice for an enterprise environment due to significant risks. Mastra's "NOASSERTION" license presents an unacceptable legal ambiguity that would not pass a compliance review. While AutoGen has a defined CC-BY-4.0 license, its development has stalled with the last commit over 80 days ago and a frequency of less than once a week. This lack of activity raises serious concerns about its long-term maintainability and support, making it a risky bet despite its high bus factor score of 9/10.
Overview
The bottom line — what this framework is, who it's for, and when to walk away.
Bottom Line Up Front
AutoGen is a Python framework for building AI agents and applications, supporting everything from no-code prototyping to scalable, distributed multi-agent systems. It features a modular design with components for core agent orchestration, conversational interactions, and integrations with external services. The framework facilitates deterministic and dynamic agentic workflows for business processes and research.
Mastra is a TypeScript framework designed for building and deploying AI agents and applications. It provides a comprehensive UI, Mastra Studio, for managing agents and workflows. The framework integrates with popular web frameworks and supports a wide array of LLM providers and models.
Best For
Building scalable multi-agent AI systems, complex agentic workflows, and multi-agent research.
Building reliable, scalable AI agents and applications across various domains.
Avoid If
Your task requires only a simple single-agent LLM call without complex interaction.
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Strengths
- +Supports rapid no-code prototyping of agents via AutoGen Studio.
- +Provides a programming framework for conversational single and multi-agent applications (AgentChat).
- +Offers an event-driven core for building scalable multi-agent AI systems and workflows.
- +Facilitates research on multi-agent collaboration and distributed agents.
- +Includes extensions for integrating with external services like OpenAI Assistant API, Docker code execution, and gRPC for distribution.
- +Supports deterministic and dynamic agentic workflows for business processes.
- +Facilitates rapid prototyping and confident shipping of AI agents.
- +Offers a comprehensive UI, Mastra Studio, for building, testing, and managing agents and workflows.
- +Provides access to over 3000 models from numerous LLM providers via its model router.
- +Supports integration with popular web frameworks like Next.js, React, Astro, Express, SvelteKit, and Hono.
- +Includes templates for various specific AI applications, from customer support to data analysis.
Weaknesses
- −Requires Python 3.10+.
- −Learning curve associated with its modular architecture (Core, AgentChat, Studio, Extensions) for complex system design.
- −Lacks first-party emphasis on local LLM integration in the provided examples, prioritizing OpenAI models.
- −Potentially complex for simple single-agent tasks, as it is designed for multi-agent systems and scalable solutions.
Project Health
Is this project alive, well-maintained, and safe to bet on long-term?
Bus Factor Score
Maintainers
Open Issues
Fit
Does it support the workflows, patterns, and capabilities your team actually needs?
State Management
no data
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Cost & Licensing
What does it actually cost? License type, pricing model, and hidden fees.
License
Perspective
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