openai-agents-python vs mastra
Two of the top projects in Agent frameworks and SDKs, side by side: who leads on each score part and who each one suits, then setup, license, activity and what each review found.
openai-agents-python
Python SDK for multi-agent workflows with handoffs, guardrails and tracing
mastra
TypeScript framework for building AI agents, workflows and MCP servers
Verdict
Both score 91; openai-agents-python ranks higher on stars, 30,614 to 29,474. Of the 4 score parts we measure for both, openai-agents-python leads on 2, mastra on 1 and 1 is even.
- Adoptionopenai-agents-python leads by 2 points, 83 to 81: close to even.
- FreshnessEven at 100.
- Maintenanceopenai-agents-python leads by 3 points, 97 to 94: close to even.
- Agent-readymastra leads by 15 points, 85 to 70: a wide gap.
Pick openai-agents-python if you are
Python developers building tool-using or multi-agent LLM apps
- Small API: Agent and Runner cover a text agent in a few lines
- Tools can be Python functions, MCP servers or hosted tools
Pick mastra if you are
TypeScript developers building production agents and workflows
- Graph workflow engine with .then(), .branch() and .parallel() control flow
- Suspend and resume agents or workflows, with execution state kept in storage
| What we compare | openai-agents-python | mastra |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 83, widely used | 81, widely used |
| Momentum | Not scored for this kind | Not scored for this kind |
| Freshness | 100, active | 100, active |
| Maintenance | 97, healthy | 94, healthy |
| Agent-ready | 70, partly | 85, ready |
| Facts from GitHub and the README | ||
| Stars | 30.6k | 29.5k |
| License | MIT (permissive) | custom license (read the license) |
| Last commit | Nov 2026 | Nov 2026 |
| Last release | Oct 2026 | Nov 2026 |
| Language | Python | TypeScript |
| Docker | No | No |
| GPU | Not needed | Not needed |
| arm64 or Apple Silicon | Not stated | Not stated |
openai-agents-python
Python library from OpenAI for building agents with instructions, tools, guardrails and handoffs between agents. It supports the OpenAI Responses and Chat Completions APIs and, per the README, 100+ other LLMs. It also includes sandbox agents, realtime and voice agents, sessions for conversation history, human-in-the-loop controls and built-in tracing.
Who it is for: Python developers building tool-using or multi-agent LLM apps
Strengths
- Small API: Agent and Runner cover a text agent in a few lines
- Tools can be Python functions, MCP servers or hosted tools
- Built-in tracing, guardrails, sessions and human-in-the-loop support
- Includes sandbox, realtime and voice agents; MIT license, Python 3.10+
Weaknesses
- Examples assume OPENAI_API_KEY; non-OpenAI models go through optional LiteLLM or any-llm
- Pull requests limited to repository collaborators
- Python only; JS/TS version is a separate repository
- Realtime agents use gpt-realtime-2.1, an OpenAI-hosted model
- no GPU
- Needs OpenAI API key, Python 3.10+, optional: Redis, optional: SQLAlchemy, optional: websockets, optional: LiteLLM or any-llm, optional: Docker
- Models: OpenAI Responses API, OpenAI Chat Completions API, 100+ other LLMs via LiteLLM or any-llm
mastra
Mastra is a TypeScript framework for building agents and graph-based workflows, with model routing across 40+ providers. It adds suspend/resume with stored state, memory, RAG, evals and observability, and runs inside React, Next.js or Node apps or as a standalone server. A local Studio on port 4111 is used to build and test agents, workflows and tools.
Who it is for: TypeScript developers building production agents and workflows
Strengths
- Graph workflow engine with .then(), .branch() and .parallel() control flow
- Suspend and resume agents or workflows, with execution state kept in storage
- Built-in evals, observability, memory and RAG alongside agents
- Can author MCP servers exposing agents and tools
Weaknesses
- TypeScript only; no other language SDKs mentioned
- Code in ee/ directories needs an enterprise license for production use
- Pull requests limited to collaborators
- No Docker or compose files in the repo
- no GPU
- Needs Node.js, LLM provider API key
- Models: OpenAI, Anthropic, Gemini, xAI, 40+ providers via model router
- port 4111
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