8 Best Agent Development Kit (ADK) Alternatives in 2026 (Open Source)
Agent Development Kit (ADK) — An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control. Applies software development principles and a graph-based runtime to AI agent creation for deterministic execution flows.
These 8 open-source tools do the same job. They are ordered by how closely they match Agent Development Kit (ADK), with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| Agent Development Kit (ADK)(original) | 21.7k | +1,807 | 2026-09-30 |
| LangChain | 147.3k | +23,455 | 2026-09-30 |
| AutoGen | 61.2k | +794 | 2026-04-06 |
| Griptape | 2.6k | +13 | 2026-09-24 |
| Agency Swarm | 4.6k | +74 | 2026-09-25 |
| Chidori | 1.4k | +4 | 2026-08-30 |
| Pydantic AI | 20.3k | +712 | 2026-09-30 |
| Microsoft Agent Framework | 13.9k | +1,157 | 2026-09-30 |
| Semantic Kernel | 28.6k | +167 | 2026-09-30 |
1. LangChain
The agent engineering platform
What sets it apart: vs other frameworks: Largest ecosystem with 100+ integrations, dual Python/JS support, backed by LangGraph for agent orchestration and LangSmith for production observability - the most widely adopted LLM framework
Best for: Building complex LLM applications with many integrations; Teams needing model interoperability and quick provider switching; Production AI applications requiring observability via LangSmith
2. AutoGen
A programming framework for agentic AI
What sets it apart: Microsoft's layered multi-agent framework (Core/AgentChat/Extensions) with no-code Studio, .NET support, and MCP integration — most enterprise-backed open-source agent framework
Best for: Building multi-agent AI systems with complex orchestration; Teams prototyping agent workflows with no-code Studio; Cross-language (Python/.NET) agent applications
3. Griptape
Modular Python framework for AI agents and workflows with chain-of-thought reasoning, tools, and memory.
What sets it apart: vs LangChain: More structured and opinionated framework with first-class Pipeline/Workflow primitives, clear driver abstraction for provider-swapping, and a companion visual no-code desktop app (Griptape Nodes)
Best for: Building enterprise AI applications with modular, swappable components; Complex multi-step workflows with parallel task execution; Teams wanting strong abstraction layers for provider independence
4. Agency Swarm
Reliable Multi-Agent Orchestration Framework
What sets it apart: Multi-agent framework modeling real-world organizational structures with directional communication flows — vs CrewAI (role-based but less control) or AutoGen (conversation-centric)
Best for: Building multi-agent systems modeled as organizational structures; Teams wanting full control over agent instructions and communication; Production multi-agent deployments with typed tools
5. Chidori
A reactive runtime for building durable AI agents
What sets it apart: vs LangGraph/CrewAI: reactive runtime with time-travel debugging and execution graph branching — enables pausing, rewinding, and exploring alternative agent paths that other orchestrators cannot do
Best for: AI agents requiring state management and execution debugging; Complex workflows needing time-travel and state branching; Development scenarios requiring rapid iteration and exploration
6. Pydantic AI
AI Agent Framework, the Pydantic way
What sets it apart: Unlike LangChain (heavy abstraction, runtime errors) or CrewAI (multi-agent focus), Pydantic AI is built by the Pydantic team to deliver FastAPI-level type safety with dependency injection, durable execution, and composable capabilities — catching errors at write-time rather than runtime.
Best for: Python developers who value type safety and want a FastAPI-like experience for building production AI agents; Teams already using Pydantic who want structured, validated LLM outputs with minimal boilerplate
7. 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
8. Semantic Kernel
Integrate cutting-edge LLM technology quickly and easily into your apps
What sets it apart: vs LangChain: enterprise-grade with native .NET/C#/Java support and Microsoft backing; vs CrewAI: more flexible plugin architecture with MCP support and process framework
Best for: Enterprise .NET/C# shops building AI agents; Multi-agent systems requiring complex orchestration; Teams already invested in Azure ecosystem
FAQ
- What are the best alternatives to Agent Development Kit (ADK)?
- The closest open-source alternatives to Agent Development Kit (ADK) are LangChain, AutoGen and Griptape, followed by Agency Swarm, Chidori and Pydantic AI. They are ranked by how closely they match what Agent Development Kit (ADK) does.
- Which Agent Development Kit (ADK) alternative is the most popular?
- LangChain has the most GitHub stars among Agent Development Kit (ADK) alternatives, with 147,320 stars.
- Which Agent Development Kit (ADK) alternative is the most actively maintained?
- By recent activity, Pydantic AI (1,381 commits in the last 90 days) is the most actively developed alternative.