Google Agent Development Kit (ADK) vs Agent 365

Detailed side-by-side comparison to help you choose the right tool

Google Agent Development Kit (ADK)

🔴Developer

AI Development Platforms

Google's open-source framework for building, evaluating, and deploying multi-agent AI systems with Gemini and other LLMs.

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Starting Price

Free

Agent 365

AI Development Platforms

Microsoft Agent 365 is a control plane for managing, securing, and governing AI agents across an organization.

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Starting Price

Custom

Feature Comparison

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FeatureGoogle Agent Development Kit (ADK)Agent 365
CategoryAI Development PlatformsAI Development Platforms
Pricing Plans4 tiers10 tiers
Starting PriceFree
Key Features
  • Multi-language SDKs: Python 2.0 Beta, TypeScript 1.0, Go, and Java
  • LLM agents, sequential, parallel, loop, and custom workflow agents
  • Built-in evaluation framework with criteria, user simulation, and environment simulation
  • Agent registry and inventory
  • Microsoft Entra identity for agents
  • Zero Trust access controls

Google Agent Development Kit (ADK) - Pros & Cons

Pros

  • Free and open source under Apache 2.0 with first-party Google support across 4 official SDKs (Python, TypeScript, Go, Java)
  • Built-in evaluation framework with trajectory accuracy, user simulation, and environment simulation — rare among the 30+ agent builders in our directory
  • Native MCP protocol support means instant integration with any MCP-compatible tool server without custom code
  • Local web UI for visual debugging of agent decision-making, tool calls, and multi-agent coordination
  • Production-ready Vertex AI Agent Engine deployment with managed scaling, plus Cloud Run and GKE options
  • Strong workflow primitives (sequential, parallel, loop) for structured multi-agent orchestration

Cons

  • Smaller third-party ecosystem than LangChain/LangGraph since the framework is only ~1 year old (launched April 2025)
  • Best experience and most advanced features are tied to Google Cloud and Gemini
  • Opinionated structure can feel restrictive for teams that prefer free-form orchestration
  • Some Gemini-optimized features (like grounding and built-in Google Search tool) don't work with non-Google models
  • Vertex AI Agent Engine deployment adds Google Cloud usage costs on top of LLM API fees

Agent 365 - Pros & Cons

Pros

  • Provides a single registry that catalogs every AI agent running across Copilot Studio, Azure AI Foundry, and third-party platforms in a Microsoft 365 tenant
  • Extends existing Microsoft Entra identity, Conditional Access, and Zero Trust policies to AI agents without requiring a separate identity stack
  • Native integration with Microsoft Purview means data loss prevention, sensitivity labels, and audit logs already cover agent activity from day one
  • Microsoft Defender coverage applies threat detection and response to agent behavior, addressing prompt injection and data exfiltration risks
  • Designed for the 400M+ Microsoft 365 commercial seats, so most enterprises can deploy without a net-new vendor procurement cycle
  • Backed by Microsoft's enterprise SLA, FedRAMP, and global compliance certifications already in place for the rest of the M365 stack

Cons

  • Enterprise-only licensing with no public pricing or self-serve tier — small teams and individual developers cannot evaluate it
  • Heavily optimized for Microsoft-built agents; governance depth for non-Microsoft agent frameworks (LangChain, CrewAI, custom Python agents) is more limited at launch
  • Requires existing investment in Microsoft Entra, Purview, and Defender to unlock the full governance value — standalone deployment offers diminished benefits
  • Newly announced in late 2025, so production references, third-party reviews, and long-term reliability data are still limited
  • Adds another administrative surface for IT teams to learn and operate alongside the existing M365 admin centers

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