8 Best OmO Alternatives in 2026 (Open Source)
OmO: Just type "mass ulw" keyword with your prompt. Now you are the master of graph engineering. Command-line agent framework with specialized graph engineering capabilities via the 'mass ulw' keyword.
These 8 open-source tools do the same job. They are ordered by how closely they match OmO, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| OmO(original) | 69.7k | +5,807 | 2026-09-30 |
| GenericAgent | 14.3k | +1,190 | 2026-09-30 |
| AgentPilot | 568 | +5 | 2025-05-15 |
| langgraph | 3.3k | +99 | 2026-09-29 |
| Agent Development Kit (ADK) | 21.7k | +1,807 | 2026-09-30 |
| GPTSwarm | 1.1k | +5 | 2026-02-05 |
| Microsoft Agent Framework | 13.9k | +1,157 | 2026-09-30 |
| PocketFlow | 11.2k | +934 | 2026-07-26 |
| MemOS | 11.7k | +972 | 2026-09-22 |
1. GenericAgent
Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption
What sets it apart: Evolves capabilities from a 3K-line seed codebase by crystallizing each task into reusable Skills rather than preloading functionality.
Best for: autonomous task execution; skill accumulation through use; minimal codebase deployments
2. AgentPilot
A versatile workflow automation platform to create, organize, and execute AI workflows, from a single LLM to complex AI-driven workflows.
What sets it apart: vs ChatGPT/Claude desktop: local multi-agent workflow builder with graph-based design, 20+ LLM providers via LiteLLM, branching chats, and built-in multi-language code interpreter
Best for: Power users building complex multi-agent workflows on desktop; Developers wanting visual graph-based agent orchestration with code execution
3. langgraph
Framework to build resilient language agents as graphs.
What sets it apart: The JavaScript/TypeScript graph-based agent framework from LangChain with built-in persistence, streaming, and human-in-the-loop — vs simpler agent libs lacking state management and controllability
Best for: Building complex, stateful JS/TS agents with controllable workflows; Production agents needing persistence, streaming, and human-in-the-loop; Teams already in the LangChain ecosystem
4. Agent Development Kit (ADK)
An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
What sets it apart: Applies software development principles and a graph-based runtime to AI agent creation for deterministic execution flows.
Best for: Developers seeking a code-first Python framework; Building complex, orchestrated agent workflows; Teams needing modular and testable agent systems
5. GPTSwarm
🐝 The First Self-Improving Agentic Solution
What sets it apart: vs CrewAI / LangGraph / OpenAI Swarm: graph-based agent framework with automatic edge optimization — agents self-organize by pruning/creating inter-agent connections, backed by ICML 2024 research
Best for: Researchers building optimizable multi-agent LLM systems; Complex tasks requiring agent coordination and graph-based workflows; Teams wanting self-improving agent swarms with edge optimization
6. Microsoft Agent Framework
A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.
What sets it apart: A production-focused, multi-language framework supporting Python, .NET, and Go with an emphasis on durability, restartability, and provider flexibility.
Best for: Teams taking agents from prototype to production; Applications requiring production-grade orchestration beyond a single prompt; Architectures needing provider flexibility and evolution
7. PocketFlow
Pocket Flow: 100-line LLM framework. Let Agents build Agents!
What sets it apart: A fully functional agent framework distilled into approximately 100 lines of core Python code.
Best for: Developers seeking a minimalist agent framework; Rapid prototyping of agent systems; Educational understanding of agent architecture
8. MemOS
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harne
What sets it apart: Provides a unified memory operating system with graph-structured memory that's inspectable and editable, not just a black-box embedding store.
Best for: AI agents needing long-term memory; multi-agent collaboration systems; developers building context-aware agents
FAQ
- What are the best alternatives to OmO?
- The closest open-source alternatives to OmO are GenericAgent, AgentPilot and langgraph, followed by Agent Development Kit (ADK), GPTSwarm and Microsoft Agent Framework. They are ranked by how closely they match what OmO does.
- Which OmO alternative is the most popular?
- Agent Development Kit (ADK) has the most GitHub stars among OmO alternatives, with 21,688 stars.
- Which OmO alternative is the most actively maintained?
- By recent activity, Agent Development Kit (ADK) (1,322 commits in the last 90 days) is the most actively developed alternative.