Collection For: Python engineers evaluating agent frameworks for production deployment

Essential Agent Frameworks for Production Python Applications

A curated selection of agent frameworks for Python teams shipping agents to production.

Production agent deployment in Python has more options than ever — and more ways to make the wrong choice. This collection covers frameworks with demonstrated production track records, active maintenance, and real community support.

Selection Criteria

Every framework in this collection meets three criteria: demonstrated production use (not just demos), active maintenance as of early 2025, and clear documentation. Frameworks that are primarily academic, abandoned, or have significant breaking-change histories were excluded.

The Collection

LangGraph

The current standard for complex, stateful agent workflows in Python. Graph-based execution model makes branching and parallel agent coordination explicit rather than implicit. Backed by LangChain Inc. with active development.

Best for: Multi-step agent workflows, human-in-the-loop patterns, complex orchestration

Maturity signal: Stable v0.2+, in production at hundreds of companies

Claude Agent SDK

Anthropic's official Python SDK for building Claude-based agents. Provides the official, maintained abstraction for tool use, structured outputs, and agent handoffs. The SDK Claude Code is built on.

Best for: Claude-based agents, teams following Anthropic's recommended patterns

Maturity signal: Official Anthropic project, actively maintained

Hermes Agent

The best choice for teams with local execution requirements. Privacy-first design, supports multiple local LLM backends, Apache 2.0 license. Less mature ecosystem than the others, but filling a real gap.

Best for: Private deployments, regulated industries, local LLM execution

Maturity signal: Beta, v0.8, production-ready for basic use cases

What We Left Out

AutoGen (Microsoft): powerful for multi-agent conversation patterns, but complex API surface and breaking changes between versions made it hard to recommend confidently. Crew AI: interesting multi-agent role abstraction, but production track record is still limited. Include both on your evaluation list if your use case involves complex multi-agent role coordination.

Framework Selection Heuristic

The question to start with is not 'which framework is best' — it's 'what does my agent need to do'. Map that to the selection criteria:

  • Need explicit workflow structure with branching? → LangGraph
  • Building on Claude, want official patterns? → Claude Agent SDK
  • Data cannot leave your infrastructure? → Hermes Agent
  • Need broad integrations with data sources? → LangChain + LangGraph

      • Items in This Collection

      Radar Hermes Agent Radar LangGraph Radar LangChain Radar Claude Agent SDK