Best AI Agent Frameworks for Developers

Stateful graph orchestration for controllable agents.

LangGraph

L

Best when agent behavior must be represented as explicit nodes, edges, state, and recovery paths.

A lightweight SDK for agents, tools, handoffs, and traces.

OpenAI Agents SDK

OA

Best when the team already standardizes on OpenAI models and wants the shortest path from prototype to observable agent workflow.

Data and retrieval framework for LLM and agent apps.

LlamaIndex

L

Best when the agent's value depends on ingestion, indexing, retrieval, and structured access to private knowledge.

Role-based multi-agent workflow framework.

CrewAI

C

Best when a workflow maps naturally to specialists, tasks, and review handoffs instead of a single state machine.

Framework for multi-agent conversations and collaboration.

Microsoft AutoGen

MA

Best for experiments where agents talk, critique, and coordinate through messages rather than a tightly controlled workflow graph.

Lightweight agent framework with a clear path from SDK to production API.

Agno

A

Best for teams that want to start with a simple agent SDK and graduate to a hosted AgentOS without a major rewrite.

AWS-native agent SDK for tool use and deployment.

Strands Agents

SA

Best for teams already on AWS who need an open-source agent SDK that integrates natively with Bedrock, Lambda, and IAM.

Cloud sandbox for agents that write code, execute commands, and handle files.

E2B

E

Best when your agent needs a safe, isolated environment to run code, install packages, and manipulate files without risking the host machine.

Natural-language browser automation backed by production cloud browsers.

Browserbase Stagehand

BS

Best when agents need to interact with web pages using natural language instead of brittle CSS selectors, with reliable cloud browser infrastructure.

Open-source software engineering agent for code, files, and terminals.

OpenHands

O

Best when you want an open-source coding agent that can read codebases, write patches, run commands, and operate in a sandboxed environment.

Google's open-source agent framework with multi-agent, A2A protocol, and production deployment.

Google Agent Development Kit

GA

Best for teams in the Google Cloud ecosystem that want a native agent framework with multi-agent orchestration, evaluation, and deployment tooling.

Type-safe agent framework for Python with structured output validation.

Pydantic AI

PA

Best for Python backend teams that want schema-aware agents where tool parameters, structured outputs, and model responses are validated at runtime against Pydantic models.

TypeScript-first agent framework with workflows, observability, and RAG.

Mastra

M

Best for TypeScript teams building agent products that need structured workflows, built-in observability, and a developer experience that matches the modern JS/TS stack.

Deploy agents at the edge on Cloudflare Workers.

Cloudflare Agents SDK

CA

Best for teams that want to run agents at the edge with ultra-low latency, leveraging Cloudflare's global network, Durable Objects for state, and AI Gateway for model routing.

Browser automation agents for complex web tasks and skill-based workflows.

browser-use

BU

Best when agents need to perform complex, multi-step browser tasks—form filling, data extraction, web app navigation—through natural language instructions rather than brittle scripts.

Loop-engineering framework: state a Goal, run judged Rounds until a read-only Verify agent settles it.

loop.js

LJ

loop.js is an open-source TypeScript framework for goal-driven agent loops. You declare a goal and verification bar; the engine runs Execute → Handoff → Verify rounds with fresh context each round, disk-backed memory, typed usd/rounds/timeout guards, crash-safe resume, and optional cron (local OS schedulers or Modal). The shipped executor uses Anthropic's Claude Agent SDK. Status is v0.2 beta (npm `@loop.js/core` 0.2.0-beta as of the July 2026 launch window).

MIT Python agent framework with memory, hybrid retrieval, RAG, MCP, and governance in one import.

agentmaker

A

agentmaker is an open-source Python framework (pip package 0.2.0, Python 3.12+) that ships a unified agent loop for chat, ReAct, plan-and-solve, and reflection, plus built-in hybrid retrieval, Mem0-style long-term memory, RAG, MCP tool loading, guardrails, human-in-the-loop approve/resume, run limits, and tracing to JSONL, SQLite, or OpenTelemetry—with local SQLite defaults and swappable backends.

Open-source multi-harness desktop agent that switches Claude Code and Codex mid-task.

Cindy

C

Cindy is an Apache-2.0 local-first agent client (GitHub `makecindy/cindy`, client v0.1.21) that unifies Claude Code and Codex harnesses—plus more in progress and a native harness brewing—so one workspace keeps memory, skills, tools, and acceptance criteria while models and harnesses switch mid-task. Bring your own keys, reuse Coding Plans, run local models, or use Cindy’s optional managed gateway; Local mode needs no Cindy sign-in for local agents.

Open-source JVM desktop harness: BYO coding agents with browser, terminal, editor, secrets, and governed MCP tools.

BOSS Console

BC

BOSS Console (BOSS) is an Apache-2.0, multi-platform operator console from Risa Labs for AI coding agents. Built with Kotlin/Compose Multiplatform on the JVM (not Electron), it runs Claude Code, Codex, Gemini CLI, or OpenCode in a workspace that includes an embedded Fluck browser, shareable BossTerm, code editor, Secret Manager, Toolbox plugins with hot-reload, and 100+ built-in `mcp__boss__*` tools with per-tool RBAC and kill-switch controls. Installers ship for macOS (Universal), Windows (x64/ARM64), and Linux (AMD64/ARM64); latest public release observed was v9.2.58 (2026-07-24).