Google Agent Development Kit (ADK) vs Omentir

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

	Google Agent Development Kit (ADK) Agents	Omentir Agents
Tagline	Google's open-source framework for building, evaluating, and deploying production AI agents	AI sales agent for automated, personalised LinkedIn outreach
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).	Freemium· Monthly: $29/month · Lifetime: $99one-time
Model	Gemini (default) plus Claude, GPT-4/5, Llama, and other providers via LiteLLM	Claude Opus 4.5
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	Automated LinkedIn cold outreachICP-based lead scoringPersonalised connection request draftingFollow-up sequencing on LinkedInUnified reply inbox triageAgency lead-gen on behalf of clientsRecruiter sourcing outreachMCP-tool integration into a broader AI agentFounder-led sales prospecting
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	Uses a current frontier model (Claude Opus 4.5) for message drafting rather than a cheap fallback MIT-licensed with full source on GitHub, so prompts and scoring logic are auditable and forkable Ships an MCP server plus Agent API so other assistants can drive outreach as a tool Collapses prospecting, sequencing, and inbox triage into a single interface instead of stitching three SaaS tools Built-in LinkedIn safety limits and human-in-the-loop review reduce account-ban risk Transparent, low entry price ($29/mo) with no per-lead metering on the Startup tier
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	LinkedIn-only — no email, X, or multichannel sequencing, so it cannot be a full sales stack on its own Automating from your own LinkedIn account still carries platform-policy risk regardless of safety limits Basic tier is capped at 50 leads/day and one campaign, which most real outbound programs will outgrow quickly Small, newer vendor with limited public deployment history compared to Apollo, Instantly, or HeyReach No native CRM — replies live in Omentir's inbox and must be exported or API-pulled into Salesforce/HubSpot Message quality still depends on the ICP prompt you write; a vague profile will produce generic outreach even with Opus 4.5
Website	google.github.io	omentir.com

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 Omentir if

✅ Uses a current frontier model (Claude Opus 4.5) for message drafting rather than a cheap fallback
✅ MIT-licensed with full source on GitHub, so prompts and scoring logic are auditable and forkable
✅ Ships an MCP server plus Agent API so other assistants can drive outreach as a tool
✅ Collapses prospecting, sequencing, and inbox triage into a single interface instead of stitching three SaaS tools

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