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You keep seeing function calling, tool use, and MCP used as if they compete. They do not. Tools are the functions, function calling is the model mechanism that calls them, and MCP is the standard that shares them across clients. Here is how the three layers stack and which to
Three terminal AI coding agents compete in 2026: Claude Code, OpenAI's Codex CLI, and Google's new Antigravity CLI after Gemini CLI retired on 18 June. This honest comparison covers the model behind each, MCP and sandbox support, and what the usable tier really costs.
MCP and A2A are the two agent protocols everyone names, but they solve different problems. MCP connects one agent to tools and data and already ships as an n8n node; A2A coordinates agents across vendors and is aimed at the enterprise. Here is what each means for a solopreneur
Stop leaving Claude Desktop to run n8n workflows by hand. The MCP Server Trigger node turns your existing workflows into callable tools so Claude and Cursor can invoke them directly.
I built the exact same order-status AI agent in n8n, Make.com, and LangChain, then compared setup effort, cost model, portability, and who each platform actually suits.
Your n8n AI agent can chat, but it cannot act beyond the nodes you hard-wired. The MCP Client Tool and MCP Server Trigger change that: one gives your agent a server's worth of tools, the other turns your workflows into tools Claude can call.
MCP servers give your AI assistant working hands: connect it to GitHub, Supabase, Zapier, and n8n with one standard protocol. First server live in about 20 minutes, free to start.
Build a Claude-powered email triage agent in n8n that classifies, labels, logs, and drafts replies without autosending, so you review only the emails that need action.
Most "AI stack" posts hide the bill. Mine runs under $10/month. Here is every tool, the exact tier, the real cost, and the job each layer does for my one-person content business.
