Comparison Preset
Neither framework is a clear choice for an enterprise environment due to significant, but different, risks. Mastra's 'NOASSERTION' license creates an unacceptable level of legal ambiguity and is a non-starter for most organizations. While SmolAgents has an enterprise-friendly Apache-2.0 license and a high bus factor score of 9/10, it carries five known vulnerabilities, one of which is rated CRITICAL. This presents a direct security risk that must be addressed before adoption. A thorough risk assessment is required, as neither can be recommended without significant legal or security remediation.
Overview
The bottom line — what this framework is, who it's for, and when to walk away.
Bottom Line Up Front
Mastra is a TypeScript framework for developing and deploying AI agents and applications. It supports rapid prototyping and confident shipping through a comprehensive toolset including Mastra Studio, an interactive UI. The framework integrates with popular web frameworks and provides access to over 3000 models from multiple LLM providers.
SmolAgents is a Python library for rapidly building LLM agents with minimal code, emphasizing simplicity. It supports both code-writing agents with sandboxed execution and traditional tool-calling, integrating flexibly with various models and tools. Its design prioritizes ease of use and broad compatibility across modalities and sources.
Best For
Building production-ready AI agents, workflows, and tools for integration into diverse applications.
Rapidly building and deploying LLM agents with code execution and flexible tool/model integration.
Avoid If
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Strengths
- +Designed to help prototype AI agents fast and ship with confidence
- +Provides Mastra Studio, an interactive UI for building, testing, and managing agents, workflows, and tools
- +Offers a model router with access to over 3000 models from various providers, including OpenAI, Anthropic, and Google
- +Supports integration into existing projects or new apps built with frameworks like Next.js, React, Astro, and Express
- +Includes pre-built templates for common use cases such as customer-facing assistants, internal copilots, and data analysis agents
- +Extremely easy to build and run agents with minimal code, designed for simplicity.
- +Supports Code Agents capable of writing actions in code, with secure sandboxed execution options (Modal, Blaxel, E2B, Docker).
- +Flexible integration with various LLM providers and models, including local Transformers and Ollama.
- +Agnostic to tool sources, allowing integration from MCP servers, LangChain, or Hugging Face Spaces.
- +Handles diverse input modalities beyond text, including vision, video, and audio inputs.
Weaknesses
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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
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Cost & Licensing
What does it actually cost? License type, pricing model, and hidden fees.
License
Perspective
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