Compare Google Agent Development Kit (ADK) with top alternatives in the ai agent builders category. Find detailed side-by-side comparisons to help you choose the best tool for your needs.
These tools are commonly compared with Google Agent Development Kit (ADK) and offer similar functionality.
AI Agents
Open-source Python framework for orchestrating role-playing, autonomous AI agents that collaborate as a 'crew' to complete complex tasks.
AI agent framework
LangGraph is LangChain's open-source framework for building stateful, durable, multi-agent workflows in Python and JavaScript with graph-based control flow.
Multi-Agent Builders
Microsoft's open-source framework for building multi-agent AI systems with asynchronous, event-driven architecture.
AI Agent Builders
AWS open-source SDK for building AI agents in Python and TypeScript with model-driven tool orchestration, multi-provider LLM support, and native AWS deployment options.
AI Agent Builders
OpenAI Agents SDK is an open-source Python framework for building agentic apps with handoffs, guardrails, sessions, tracing, MCP tools, sandbox agents, and realtime voice agents.
Other tools in the ai agent builders category that you might want to compare with Google Agent Development Kit (ADK).
AI Agent Builders
Microsoft Agent 365 is a control plane for managing, securing, and governing AI agents across an organization.
AI Agent Builders
Open API specification providing a common interface for communicating with AI agents, developed by AGI Inc. to enable easy benchmarking, integration, and devtool development across different agent implementations.
AI Agent Builders
Curated collections of tested prompts, templates, and best practices for maximizing productivity with AI coding assistants like ChatGPT, Claude, GitHub Copilot, and Cursor.
AI Agent Builders
AI-powered spreadsheet assistant that generates complex Excel and Google Sheets formulas instantly using AI technology and plain English instructions.
AI Agent Builders
Apple's personal intelligence system built into iOS, iPadOS, and macOS that provides AI-powered features for writing, communication, and productivity.
AI Agent Builders
Lightweight, modular Python framework for building AI agents with Pydantic-based type safety, provider-agnostic LLM integration, and atomic component design for maximum control and debuggability.
💡 Pro tip: Most tools offer free trials or free tiers. Test 2-3 options side-by-side to see which fits your workflow best.
ADK is more opinionated and ships with a built-in evaluation framework, local debugging UI, and structured workflow agent types (sequential, parallel, loop) out of the box, whereas LangChain/LangGraph are more flexible and modular with a larger third-party ecosystem. ADK also provides four official language SDKs (Python, TypeScript, Go, Java) versus LangChain's Python and JavaScript. Choose ADK for structured multi-agent development with Google Cloud integration; choose LangChain/LangGraph for maximum flexibility and community ecosystem breadth.
Yes. ADK supports any LLM through LiteLLM integration, and the documentation explicitly lists Anthropic Claude, Ollama, vLLM, LiteRT-LM, and Apigee AI Gateway as supported model providers alongside Gemini and Gemma. However, some Gemini-optimized features like built-in Google Search grounding are only available when using Google models.
No. ADK runs entirely locally for development and includes a local web UI, CLI, and API server runtime. You can also deploy to any container platform including Cloud Run, GKE, or non-Google clouds via standard Docker containers. Google Cloud and Vertex AI Agent Engine are optional managed deployment targets, not requirements.
ADK ships in four official SDKs: Python (currently 2.0 Beta with workflow agents and agent teams), TypeScript 1.0 (newly released in 2026 — making ADK one of the few enterprise agent frameworks with first-party TypeScript support), Go, and Java. The Python 2.0 Beta introduces new workflow primitives, ambient agents, resumable runs, and cancelable execution.
ADK ships with a comprehensive evaluation framework that includes criteria-based scoring, user simulation (synthetic user interactions), environment simulation (mocked tools and external systems), and custom metrics. It also offers an optimization module for iterative improvement, allowing teams to systematically test and refine agent quality before production deployment.
Compare features, test the interface, and see if it fits your workflow.