microsoft/agent-framework Alternatives

choose if you need a Python-only multi-agent harness without .NET/Go support.

Multi-Agent Harness for Production AI

choose if you require a TypeScript agent framework, which the seed does not offer.

AI Agent Engineering Platform built on an Open Source TypeScript AI Agent Framework

choose if you need a Java agent framework for distributed long-running agents.

Build distributed, production-grade, long-running agents.

choose if you want a TypeScript runtime harness focused on turning an LLM into a working agent.

The open-source agent harness - the runtime layer that turns an LLM into a working agent.

choose if you need a Rust-core agent framework with Python wrapper for performance-sensitive workloads.

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.

choose if you want a Go-native, event-driven agent framework with MCP tool discovery.

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.

choose if you want a minimal, low-overhead framework directly from OpenAI.

A lightweight, powerful framework for multi-agent workflows

choose if you want Google's code-first Python toolkit with built-in evaluation and deployment support.

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

choose if you want fine-grained graph control, persistence, and human-in-the-loop from the LangChain ecosystem.

Build resilient agents.

choose if you want a ready-made batteries-included agent harness from LangChain.

The batteries-included agent harness.

choose if you need a Java-based enterprise workflow platform for SuperAgents.

Enterprise-grade, commercial-friendly agentic workflow platform for building next-generation SuperAgents.

choose if you want Google's code-first agent toolkit in Go.

An open-source, code-first Go toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

choose if you want the AutoGen lineage with an all-in-one agent OS.

AG2 (formerly AutoGen): The Open-Source AgentOS.Join us at: https://discord.gg/sNGSwQME3x

choose if you want an enterprise-grade multi-agent orchestration framework with extra tooling.

The Enterprise-Grade Multi-Agent Orchestration Framework. Website: https://swarms.ai

choose if you are in a Java/Spring ecosystem and need agentic AI framework integration.

Agentic AI Framework for Java Developers

choose if you must orchestrate multiple existing agent CLIs under one policy/sandbox layer.

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.

choose if you prefer a lightweight MCP-protocol-based workflow engine over graph orchestration.

Build effective agents using Model Context Protocol and simple workflow patterns

choose if you want to build a custom agent harness with a low-level SDK rather than adopt a full framework.

Build an agent harness and control it end-to-end. Open-source SDK for production AI agents in Python & TypeScript - any model, any cloud.

choose if you prefer a planner/plugin-based SDK for integrating LLMs into existing apps.

Integrate cutting-edge LLM technology quickly and easily into your apps

choose if you want event-driven multi-agent orchestration over a message bus.

An event-driven framework designed to build and orchestrate multi-agent AI systems. It enables seamless integration of AI agents with real-world data sources and systems, facilitating complex, multi-step workflows.

choose if you need a memory-first harness with self-improving deep research capabilities.

The Harness of Harnesses: a trusted, persistent, self-evolving multi-agent ecosystem for all-domain collaboration.

choose if you want pipeline-based orchestration with explicit retrieval/context control.

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.

choose if you need a low-level Rust framework for LLM applications and are willing to implement agent orchestration yourself.

⚙️🦀 Build modular and scalable LLM Applications in Rust

choose if you prefer a graphical platform for creating and managing agents rather than a code-first framework.

Evo AI is an open-source platform for creating and managing AI agents, enabling integration with different AI models and services.