AI agent SDKs, platforms & frameworks

The agent layer of the AI stack — from SDKs you ship in code (OpenAI, Claude) to no-code platforms (Lindy, Dify) and orchestration frameworks (LangChain, CrewAI). Each review covers pricing, lock-in, and what you should pair it with.

Choose the model first

Decide whether the work needs an agent before choosing a framework

Start with the execution boundary, then narrow the framework and deployment choice.

AutoGen

framework open-source

Microsoft's maintenance-mode multi-agent framework — preserve existing systems or plan migration to Microsoft Agent Framework.

Claude Agent SDK

sdk free

Build agents with tool use, computer use, MCP, and Anthropic's safety primitives — Python and TypeScript.

CrewAI

framework open-source

OSS framework for orchestrating role-playing AI agents that collaborate on complex tasks — Python-first.

Dify

platform freemium

Self-hostable platform for agentic AI apps — RAG pipelines, agent workflows, and model management in one stack.

Flowise

platform open-source

Archived visual builder for LLM agents and chatflows — self-hostable for teams with an explicit maintenance plan.

LangChain

framework open-source

Open-source framework ecosystem for LLM applications, with LangGraph for stateful orchestration.

Langflow

platform open-source

Open-source Python visual builder for AI applications, agents, RAG, and MCP flows, with core components and provider bundles.

LangGraph

framework open-source

Low-level graph-based agent orchestration from the LangChain team — explicit state, loops, and human-in-the-loop control.

Lindy

no-code freemium

No-code AI assistants for sales, support, and operations workflows across email, meetings, and calls.

OpenAI Agents SDK

sdk free

Lightweight framework for multi-agent workflows with handoffs, guardrails, and tool calls — Python and TypeScript.