MCP, Apify, or Custom Agents: A Developer's Guide to Choosing the Right LLM Tool
Developer Marek Cziba outlines the key differences between three approaches teams use to give LLMs the ability to act: MCP servers, Apify actors, and custom agents. MCP (Model Context Protocol) is best suited for exposing deterministic, single-call capabilities to multiple AI clients through one standardised integration. Apify, a hosted cloud platform, is the stronger choice for large-scale web scraping tasks where proxy networks, browser automation, and bot-detection handling are required without building that infrastructure in-house. Custom agents — developer-owned code loops that call LLMs and execute logic iteratively — are recommended when workflows involve multi-step decisions, stateful business rules, or complex orchestration that neither MCP nor Apify supports natively. Cziba stresses that the three tools are not interchangeable, and selecting the wrong one can cost weeks of rework, while the right choice can deliver a working product in days.
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