Comparison
openai-agents-python vs agency
openai-agents-python (A lightweight, powerful framework for multi-agent workflows) vs agency (A fast and minimal framework for building agentic systems.) - live GitHub stats and typed graph relationships, not marketing.
Markdown twin · openai-agents-python alternatives · agency alternatives
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Tagline
- openai-agents-python
- A lightweight, powerful framework for multi-agent workflows
- agency
- A fast and minimal framework for building agentic systems.
Stars
- openai-agents-python
- 28k
- agency
- 487
Forks
- openai-agents-python
- 4.3k
- agency
- 28
Open issues
- openai-agents-python
- 65
- agency
- 19
Language
- openai-agents-python
- Python
- agency
- Python
Adopt for
- openai-agents-python
- A flexible and lightweight framework for building complex multi-agent systems capable of integrating with multiple LLMs.
- agency
- Agency provides an Actor model framework that enables the development of custom agent-based applications with support for concurrency, networked agents through AMQP, and detailed observability features.
Persona
- openai-agents-python
- -
- agency
- -
Runtime
- openai-agents-python
- -
- agency
- -
License
- openai-agents-python
- MIT
- agency
- MIT
Last pushed
- openai-agents-python
- Jul 8, 2026
- agency
- Jun 10, 2026
Categories
- openai-agents-python
- AI Agents
- agency
- AI Agents
Trust and health
Maintenance
- openai-agents-python
- Very active (96%)
- agency
- Active (82%)
Days since push
- openai-agents-python
- 0d
- agency
- 27d
Open issues (now)
- openai-agents-python
- 65
- agency
- 19
Owner type
- openai-agents-python
- Organization
- agency
- User
Security scan
- openai-agents-python
- No lockfile
- agency
- 5 low (5 low)
Full report
- openai-agents-python
- Trust report
- agency
- Trust report
Typed relationship
openai-agents-python alternative agencyBoth Agency and OpenAI Agents Python address multi-agent workflows but offer different design approaches, making them alternative frameworks for similar purposes.
Shared compatibility
- Python · openai-agents-python: Python runtime · agency: Python runtime
Choose openai-agents-python if…
- Both Agency and OpenAI Agents Python address multi-agent workflows but offer different design approaches, making them alternative frameworks for similar purposes.
- Tags unique to openai-agents-python: llm, python, openai.
- - When you need a provider-agnostic solution that supports over 100 different Language Models including OpenAI's.
When NOT to use openai-agents-python
- - When you prefer a more specialized solution specifically tailored for simpler agent workflows without comprehensive multi-agent capabilities.
- - If you are solely working with frameworks or LLMs that do not integrate well or at all with the OpenAI responses and Chat Completions APIs.
- - For projects requiring minimalistic setup; if your project can be handled efficiently by a less complex tool or framework.
Choose agency if…
- Pricing: The framework is available under an MIT license, making it free to use. However, advanced services like detailed support or commercial customizations might require a contract with additional costs..
- Requirements: Min 1 GB RAM; Requires Docker; Docker is used for deployment but not mandatory; the framework can be set up in any environment that supports Python and potentially RabbitMQ for networked use..
- Both Agency and OpenAI Agents Python address multi-agent workflows but offer different design approaches, making them alternative frameworks for similar purposes.
- Tags unique to agency: llmops, machine-learning, actor-model, agi.
- - You need to develop a system where agents can be integrated in a concurrent or distributed environment using Python.
When NOT to use agency
- - If your primary requirement is to implement generic AI functionalities without focusing on agent interaction and custom architectures, preferring simplicity over flexibility.
- - For systems requiring extremely high performance for processing large datasets where overhead from the agentic model might introduce unacceptable latency.
Explore
openai-agents-python trust report →agency trust report →AI Agents category →All comparisonsStack workflowsTrending tools
Related comparisons
Common questions
- What is the difference between openai-agents-python and agency?
- openai-agents-python: A lightweight, powerful framework for multi-agent workflows. agency: A fast and minimal framework for building agentic systems.. See the comparison table for live GitHub stats and shared categories.
- When should I choose openai-agents-python over agency?
- Choose openai-agents-python over agency when Both Agency and OpenAI Agents Python address multi-agent workflows but offer different design approaches, making them alternative frameworks for similar purposes; Tags unique to openai-agents-python: llm, python, openai; - When you need a provider-agnostic solution that supports over 100 different Language Models including OpenAI's.
- When should I choose agency over openai-agents-python?
- Choose agency over openai-agents-python when Pricing: The framework is available under an MIT license, making it free to use. However, advanced services like detailed support or commercial customizations might require a contract with additional costs.; Requirements: Min 1 GB RAM; Requires Docker; Docker is used for deployment but not mandatory; the framework can be set up in any environment that supports Python and potentially RabbitMQ for networked use.; Both Agency and OpenAI Agents Python address multi-agent workflows but offer different design approaches, making them alternative frameworks for similar purposes; Tags unique to agency: llmops, machine-learning, actor-model, agi; - You need to develop a system where agents can be integrated in a concurrent or distributed environment using Python.
- When should I avoid openai-agents-python?
- - When you prefer a more specialized solution specifically tailored for simpler agent workflows without comprehensive multi-agent capabilities. - If you are solely working with frameworks or LLMs that do not integrate well or at all with the OpenAI responses and Chat Completions APIs. - For projects requiring minimalistic setup; if your project can be handled efficiently by a less complex tool or framework.
- When should I avoid agency?
- - If your primary requirement is to implement generic AI functionalities without focusing on agent interaction and custom architectures, preferring simplicity over flexibility. - For systems requiring extremely high performance for processing large datasets where overhead from the agentic model might introduce unacceptable latency.
- Is openai-agents-python or agency more popular on GitHub?
- openai-agents-python has more GitHub stars (27,732 vs 487). Stars measure visibility, not whether either tool fits your constraints.
- Are openai-agents-python and agency open source?
- Yes - both are open-source projects on GitHub (openai-agents-python: MIT, agency: MIT).
- Where can I find alternatives to openai-agents-python or agency?
- GraphCanon lists graph-backed alternatives at /tools/openai-openai-agents-python/alternatives and /tools/operand-agency/alternatives (/tools/openai-openai-agents-python/alternatives.md, /tools/operand-agency/alternatives.md), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at /compare/openai-openai-agents-python-vs-operand-agency.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, openai-agents-python or agency?
- openai-agents-python: Very active. agency: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for openai-agents-python and agency?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: openai-agents-python: /tools/openai-openai-agents-python/trust; agency: /tools/operand-agency/trust.