Google Agent Development Kit (ADK) vs Scrapling

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

	Google Agent Development Kit (ADK) Agents	Scrapling Agents
Tagline	Google's open-source framework for building, evaluating, and deploying production AI agents	Adaptive Python web-scraping framework with a built-in MCP server for AI coding agents.
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).	Free· Free and open source under BSD-3-Clause. Self-hosted Python library with no paid tier or hosted service; users pay only for their own infrastructure, browsers, and any proxies or LLM tokens they choose to plug in.
Model	Gemini (default) plus Claude, GPT-4/5, Llama, and other providers via LiteLLM	—
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	MCP-driven web scraping from Claude DesktopAgent-powered research and browsingSelf-healing product and price monitorsCloudflare-protected page extractionShopify and e-commerce catalog scrapingSitemap-driven large-scale crawlsRAG data collection pipelinesScreenshot capture for visual LLM analysisConcurrent multi-session crawling
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	Adaptive selectors that self-heal when the target site's DOM changes, reducing scraper maintenance Built-in MCP server turns any MCP-aware assistant (Claude, Cursor) into a scraping agent with browser sessions and screenshots Bundles fetching, parsing, stealth browser automation, and a Scrapy-style Spider API in one library Ships anti-bot features including Cloudflare Turnstile bypass, fingerprint spoofing, and CDP remote-browser control Open source under BSD-3-Clause with 92% test coverage and full Python type hints Trims scraped content before handing it to the LLM, cutting token usage on agentic workflows Supports modern transports including HTTP/3 and Playwright-driven Chromium/Chrome
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	Python-only; no first-party Node, Go, or hosted SaaS option Requires Python 3.10+ and separately-installed browser and fetcher extras or you get ModuleNotFoundError You still supply and run your own proxies, CAPTCHA solvers, and browser infrastructure at scale Anti-bot arms race means adaptive selectors and stealth features will drift as sites update defenses No managed dashboard, scheduler, or team-collaboration UI; everything is code-first Documentation names Claude and Cursor explicitly but is thin on other MCP hosts and end-to-end agent examples
Website	google.github.io	scrapling.readthedocs.io

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 Scrapling if

✅ Adaptive selectors that self-heal when the target site's DOM changes, reducing scraper maintenance
✅ Built-in MCP server turns any MCP-aware assistant (Claude, Cursor) into a scraping agent with browser sessions and screenshots
✅ Bundles fetching, parsing, stealth browser automation, and a Scrapy-style Spider API in one library
✅ Ships anti-bot features including Cloudflare Turnstile bypass, fingerprint spoofing, and CDP remote-browser control

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