Google Agent Development Kit (ADK) vs Lindy

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Google Agent Development Kit (ADK) Agents	Lindy Agents
Tagline	Google's open-source framework for building, evaluating, and deploying production AI agents	No-code AI agents for email, meetings, and the rest of your admin work
Category	Agents	Agents
Pricing	Free· Framework itself is free and open-source (Apache 2.0). Costs come from the underlying model provider (e.g. Gemini API / Vertex AI usage) and any hosting infrastructure (Cloud Run, GKE, Agent Engine).	Paid· Human assistant: $8,000 · Plus: $49.99 · Pro: $99.99 · Max: $199.99 · Enterprise: Contact sales
Model	Gemini (default) plus Claude, GPT-4/5, Llama, and other providers via LiteLLM	Frontier LLMs (Anthropic Claude and OpenAI GPT families) selected per task; not user-configurable
Editorial score	—	—
Use cases	Multi-agent research assistantCustomer support triage agentRAG chatbot backed by Vertex AI SearchCode review and refactoring agentBigQuery natural-language analytics agentDocument processing pipelineVoice/streaming conversational agentInternal tool-use agent orchestrating APIsEvaluation and regression testing of LLM workflowsEnterprise workflow automation on Agent Engine	AI executive assistantInbox triage and email draftingMeeting scheduling over emailMeeting notes and action-item extractionSDR outbound and lead qualificationRecruiting inbound triage and interview bookingCRM data entry and enrichmentCustomer support ticket autoresponseMulti-step workflow automationBrowser computer-use for API-less sites
Pros	Genuinely open-source (Apache 2.0) with active Google engineering behind it, not a hosted-only product Multi-language: first-class Python, Java, and Go SDKs — rare among agent frameworks that are usually Python-only Built-in dev UI (`adk web`) with trace inspection, event stream, and session replay speeds up debugging enormously Model-agnostic via LiteLLM — Gemini is default but Claude, GPT, and local models plug in cleanly Rich multi-agent primitives out of the box: SequentialAgent, ParallelAgent, LoopAgent, and hierarchical sub-agents Tight Google Cloud integration for deployment (Cloud Run, GKE, Agent Engine) plus native BigQuery/Vertex Search tools Evaluation harness with trajectory-level scoring is included, not a separate paid add-on First-class MCP (Model Context Protocol) client and server support	Visual, no-code agent builder with triggers, branches, and inter-agent hand-offs — non-developers ship working automations quickly Deep first-party integrations with Gmail, Google Calendar, Slack, HubSpot, Salesforce, Zoom, and 3,000+ apps Meeting agent that can join Zoom/Meet calls, transcribe, extract action items, and push them into your CRM or task tracker SMS/iMessage and phone-call channels let you delegate to a Lindy without opening the web app Higher-tier computer-use agent handles sites and workflows that have no API Enterprise controls (SSO/SCIM, HIPAA, shared usage pool, dedicated onboarding) suitable for regulated teams Shared memory across agents so a contact recognised by one Lindy is remembered by the others
Cons	Documentation and examples lean heavily on Gemini + Google Cloud; non-Google paths work but feel like second-class citizens API surface is still evolving — breaking changes between minor versions have been common through 2025-2026 Multi-agent orchestration primitives are powerful but the graph/callback model has a real learning curve compared to a plain prompt loop Agent Engine deployment is convenient but locks you into GCP billing and quotas TypeScript/Kotlin support lags the Python SDK in features and community examples	No free tier — after the 7-day trial every seat is a real monthly cost, and heavier automations push you up the tiers fast Task-credit meter can be opaque; long-running or computer-use flows burn usage in ways that are hard to predict in advance Closed-source and cloud-only — no self-hosted option, and you cannot pin or swap the underlying model Public developer API and webhooks-as-a-first-class-citizen are limited compared with orchestration frameworks like n8n or LangGraph Reliability on long agentic chains still requires human review, especially for outbound email sent in your voice Pricing is per-inbox rather than per-seat, which gets awkward for teams with shared mailboxes
Website	google.github.io	www.lindy.ai

Pick Google Agent Development Kit (ADK) if

✅ Genuinely open-source (Apache 2.0) with active Google engineering behind it, not a hosted-only product
✅ Multi-language: first-class Python, Java, and Go SDKs — rare among agent frameworks that are usually Python-only
✅ Built-in dev UI (`adk web`) with trace inspection, event stream, and session replay speeds up debugging enormously
✅ Model-agnostic via LiteLLM — Gemini is default but Claude, GPT, and local models plug in cleanly

Pick Lindy if

✅ Visual, no-code agent builder with triggers, branches, and inter-agent hand-offs — non-developers ship working automations quickly
✅ Deep first-party integrations with Gmail, Google Calendar, Slack, HubSpot, Salesforce, Zoom, and 3,000+ apps
✅ Meeting agent that can join Zoom/Meet calls, transcribe, extract action items, and push them into your CRM or task tracker
✅ SMS/iMessage and phone-call channels let you delegate to a Lindy without opening the web app

Compare a different pair →