AI agent framework / agent harness
DeepAgents is an opinionated agent harness built on LangGraph for long-horizon, multi-step autonomous work with sub-agents, filesystem/shell access, memory, and human-in-the-loop.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
Code-first agent framework from Google; choose it for first-party Google ecosystem and Apache-2.0 licensing.
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
Distributed multi-agent framework in Java; choose it for long-running JVM-native agents.
Build distributed, production-grade, long-running agents.
Rust-core multi-agent framework with Python wrapper; choose it when performance and security are critical.
GraphBit is the world’s first enterprise-grade Agentic AI framework, built on a Rust core with a Python wrapper for unmatched speed, security, and scalability. It enables reliable multi-agent workflows with minimal CPU and memory usage, making it production-ready for real-world enterprise environments.
Go agent framework with event-driven workflows; choose it for a native Go stack.
Open-source Agentic AI framework in Go for building, orchestrating, and deploying intelligent agents. LLM-agnostic, event-driven, with multi-agent workflows, MCP tool discovery, and production-grade observability.
Graph+loop agent framework on LangGraph; choose it for Dify DSL support and fine-grained workflow-graph control.
Graph-Orchestrated Agent Loop — a production-grade framework on LangGraph. Combine workflow graphs and agent loops, transpile Dify DSL to runnable code, swap wire protocols (Dify/OpenAI).
Lightweight official OpenAI multi-agent framework; choose it for first-class OpenAI tooling and a minimal core.
A lightweight, powerful framework for multi-agent workflows
Memory-first agent harness with deep-research tools; choose it if persistent memory and self-improvement are top priorities.
The Harness of Harnesses: a trusted, persistent, self-evolving multi-agent ecosystem for all-domain collaboration.
Microsoft's cross-language agent and multi-agent framework; choose it for .NET plus Python coverage.
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
Production-focused multi-agent harness; choose it for cloud-native deployment and fleet management.
Multi-Agent Harness for Production AI
Minimal agent-harness runtime layer; choose it if you want a lean, embeddable harness.
The open-source agent harness - the runtime layer that turns an LLM into a working agent.
Solves the same problem with a different architecture or at a different layer. Expect to rewrite the integration.
Meta-harness that orchestrates multiple agent backends; choose it when you need to swap or centrally manage different harnesses.
Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents — swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device.
Enterprise Java workflow platform with visual tooling; choose it for a Java-based governance stack.
Enterprise-grade, commercial-friendly agentic workflow platform for building next-generation SuperAgents.
Older TypeScript agent management platform; choose it if you need a web UI over multiple models.
Evo AI is an open-source platform for creating and managing AI agents, enabling integration with different AI models and services.
Broader LLM SDK for embedding AI into applications; choose it when you need tight app integration rather than a standalone agent.
Integrate cutting-edge LLM technology quickly and easily into your apps
TypeScript agent engineering platform; choose it if you want a visual engineering workflow.
AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework
MCP-centric agent builder with simple workflow patterns; choose it if you standardize on Model Context Protocol.
Build effective agents using Model Context Protocol and simple workflow patterns
SDK for building your own harness end-to-end; choose it when you need total control instead of a prebuilt agent.
Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.
Does the same job, but ships as an app. Useful to a person, not swappable into a codebase.
Personal AI agent rather than a developer harness; choose it if you want a ready-made assistant.
The agent that grows with you
Self-hosted personal assistant with WebUI and chat; choose it for an ultra-lightweight ready-to-use assistant.
Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps
Assistant-style harness with one-line install; choose it for an out-of-the-box personal assistant, not a library.
Open-source super AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-agent, multi-model, multi-channel. Lightweight, extensible, one-line install. (formerly chatgpt-on-wechat)
Personal AI assistant with computer/browser-use; choose it for an end-user assistant.
⚡️next-generation personal AI assistant powered by LLM, RAG and agent loops, supporting computer-use, browser-use and coding agent, demo: https://demo.openagentai.org
Go port of a personal AI assistant; choose it for a self-hosted assistant with multi-tenant isolation.
GoClaw - GoClaw is OpenClaw rebuilt in Go — with multi-tenant isolation, 5-layer security, and native concurrency. Deploy AI agent teams at scale without compromising on safety.
These projects were analysed and named deepagents among their alternatives. The relationship is not symmetric — how deepagents rates them is a separate judgement, made when deepagents is analysed in its own right.
calls deepagents “when you want a LangChain-native harness with the same sub-agent architecture and tighter LangChain ecosystem integration.”
An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
calls deepagents “choose if you want a batteries-included agent harness from the LangChain ecosystem, with LangGraph integration, instead of CowAgent's own harness.”
Open-source super AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-agent, multi-model, multi-channel. Lightweight, extensible, one-line install. (formerly chatgpt-on-wechat)
calls deepagents “Choose when you want a Python agent harness tightly integrated with LangChain's ecosystem and prebuilt tools.”
A lightweight, powerful framework for multi-agent workflows
calls deepagents “choose for a batteries-included agent harness with tools and multi-agent support out of the box.”
Integrate cutting-edge LLM technology quickly and easily into your apps
calls deepagents “batteries-included Python agent harness; choose for opinionated policies built on LangGraph.”
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
calls deepagents “choose if you want a ready-made batteries-included agent harness from LangChain.”
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
calls deepagents “Choose it if you already use LangChain and want a batteries-included harness with deep ecosystem integration.”
PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute tasks. Deployed in 5 lines of code with built-in memory, RAG, and support for 100+ LLMs.
calls deepagents “Use when you are committed to the LangChain/LangGraph stack and want a batteries-included harness instead of seed's standalone SDK.”
Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.
calls deepagents “batteries-included harness integrated with LangChain; choose for LangChain-centric stacks.”
The Harness of Harnesses: a trusted, persistent, self-evolving multi-agent ecosystem for all-domain collaboration.
calls deepagents “Batteries-included agent harness library for LangChain ecosystem; use when building agents with LangChain tools and structured prompts.”
The agent that grows with you
calls deepagents “Batteries-included LangGraph harness; choose when you want prebuilt agent skills in code.”
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
calls deepagents “Choose for a batteries-included LangGraph-based agent harness within the LangChain ecosystem.”
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
calls deepagents “LangChain-based harness; use when you need deep ecosystem integration rather than a turnkey assistant.”
Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps
calls deepagents “Choose when you want a batteries-included production harness built on LangGraph.”
Build, run, and manage agent platforms.
calls deepagents “Batteries-included harness for LangChain agents, speeds up coding but requires LangChain experience.”
ToolJet is the open-source foundation of ToolJet AI - the enterprise app generation platform for building internal tools, dashboard, business applications, workflows and AI agents 🚀
calls deepagents “Choose for a batteries-included agent harness from the LangChain ecosystem for dev-heavy agent workflows.”
Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities.
calls deepagents “Choose for a batteries-included harness built on LangGraph with prebuilt tools.”
Sim is the collaborative workspace to build, deploy, and monitor AI agents and workflows. Used by 100,000+ builders.
calls deepagents “batteries-included harness for agentic coding, narrower than general LLM orchestration; choose for code-generation agents.”
Open-source AI orchestration framework for building context-engineered, production-ready LLM applications. Design modular pipelines and agent workflows with explicit control over retrieval, routing, memory, and generation. Built for scalable agents, RAG, multimodal applications, semantic search, and conversational systems.
calls deepagents “Choose when you want a batteries-included agent harness based on LangChain.”
AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
calls deepagents “batteries-included harness for agent engineering; use it for production-grade code-first agents.”
An AI agent development platform with all-in-one visual tools, simplifying agent creation, debugging, and deployment like never before. Coze your way to AI Agent creation.