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DIDATTICO","\u003Ch1 class=\"fw-semibold text-uppercase\">Model Context Protocol\u003C/h1>\n","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">Impara il Model Context Protocol, lo standard aperto di Anthropic per collegare gli agenti AI a strumenti e dati, e costruisci i tuoi server MCP in Python.\u003C/span>\u003C/p>\n","\u003Ch2>Descrizione\u003C/h2>\n\u003Cp class=\"font-size-body-1\">La guida completa al Model Context Protocol (MCP): impari lo standard aperto di Anthropic e lo trasformi in server MCP reali, integrati con Claude, LangChain, OpenAI Agents SDK e n8n.\u003C/p>\n",{"title":806,"list":807,"link":800},"DOMANDE FREQUENTI",[808,811,814,817,820,823,826,829,832,835,838,841],{"title":809,"text":810},"Cos'è il Model Context Protocol (MCP) e a cosa serve?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">Il Model Context Protocol è uno standard aperto che definisce un modo unico per collegare i modelli linguistici (LLM) a strumenti, dati e servizi esterni. Serve a superare i due limiti strutturali di un LLM (conoscenza ferma ai dati di addestramento e incapacità di compiere azioni oltre la generazione di testo) offrendo un’interfaccia unificata al posto di tante integrazioni custom. La documentazione ufficiale lo descrive come “una porta USB-C per le applicazioni di intelligenza artificiale”.\u003C/span>\u003C/p>\n",{"title":812,"text":813},"Chi ha creato MCP e quando?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">MCP è stato sviluppato da Anthropic e reso pubblico come standard aperto a fine novembre 2024. Da allora è stato adottato da gran parte dell’ecosistema AI: OpenAI (nell’Agents SDK), Google e Microsoft, oltre ai principali strumenti di sviluppo come VS Code, Cursor e GitHub Copilot.\u003C/span>\u003C/p>\n",{"title":815,"text":816},"Che differenza c'è tra MCP e una normale API?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">Un’API espone le funzionalità di un singolo servizio con le sue convenzioni, i suoi formati e la sua autenticazione. MCP non sostituisce le API: le standardizza verso l’LLM. Invece di scrivere un’integrazione diversa per ogni coppia modello-servizio (un problema M×N), ogni host e ogni server implementano lo standard MCP una sola volta (un problema M+N), riducendo la complessità e rendendo le soluzioni più portabili e manutenibili.\u003C/span>\u003C/p>\n",{"title":818,"text":819},"Qual è la differenza tra MCP e il tool/function calling?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">Il tool (o function) calling è il meccanismo con cui un LLM decide di invocare una funzione; MCP è il protocollo che standardizza come quelle funzioni e le risorse e i prompt, vengono esposte e scoperte, indipendentemente dal framework che usi. Nel corso vedi entrambe le cose in azione: come un server espone i tool e come un agente li scopre e li invoca.\u003C/span>\u003C/p>\n",{"title":821,"text":822},"Cos'è un server MCP e come funziona l'architettura client-server?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">MCP segue il paradigma client-server: un Host (es. Claude Desktop, un IDE, un agente) contiene uno o più Client, ciascuno con una connessione 1:1 a un Server MCP. Il server espone capabilities (tools, risorse e prompt) verso risorse locali (file, database) o remote (API, servizi). Nel corso costruisci sia i server sia gli host che li consumano.\u003C/span>\u003C/p>\n",{"title":824,"text":825},"Serve saper programmare? Quali sono i prerequisiti?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">Per la parte di costruzione dei server serve una conoscenza di base di Python, perché usiamo la libreria FastMCP. La parte finale su n8n, invece, mostra come lavorare con MCP anche in una piattaforma visuale di automation, avvicinando lo standard anche a chi predilige un approccio low-code.\u003C/span>\u003C/p>\n",{"title":827,"text":828},"Cos'è FastMCP e perché si usa nel corso?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">FastMCP è la libreria Python più diffusa per costruire server (e client) MCP in modo rapido: dichiari i tool come normali funzioni Python e la libreria genera schema e validazione. Nel corso la usiamo per realizzare da zero server MCP custom ed esplorare i diversi metodi di trasporto.\u003C/span>\u003C/p>\n",{"title":830,"text":831},"Il corso copre l'integrazione con LangChain e con l'OpenAI Agents SDK?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">Sì, ed è uno degli elementi che lo distinguono: gran parte dei contenuti disponibili si ferma a Claude Desktop, mentre qui colleghi gli stessi server MCP prima a LangChain e poi all’OpenAI Agents SDK, imparando a integrare lo standard nei due framework più usati per costruire agenti.\u003C/span>\u003C/p>\n",{"title":833,"text":834},"Posso usare MCP senza scrivere codice, con strumenti come n8n?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">Un intero modulo è dedicato a MCP dentro n8n, la piattaforma di automation open source. Vedrai n8n nel ruolo di client MCP (con Smithery e con il server ufficiale di GitHub) e poi nel ruolo di server MCP consumato da Claude Desktop: è il modo per portare MCP anche in workflow no-code e low-code.\u003C/span>\u003C/p>\n",{"title":836,"text":837},"Il corso è aggiornato sui metodi di trasporto? SSE è ancora valido?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">Sì. Il corso tratta in modo sistematico i tre trasporti (Stdio, Streamable HTTP e SSE) spiegando perché SSE standalone è ormai deprecato in favore di Streamable HTTP, così lavori sempre con l’approccio corrente e consigliato.\u003C/span>\u003C/p>\n",{"title":839,"text":840},"In cosa si differenzia questo corso dai tanti tutorial gratuiti su MCP?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">La maggior parte dei contenuti gratuiti si ferma alla teoria o alla costruzione di un primo server con Claude Desktop. Questo è un percorso completo e in italiano che va dalla teoria ai server custom, alle integrazioni con LangChain e OpenAI Agents SDK, ai server di terze parti, all’intero ecosistema Claude e a MCP dentro n8n in modo bidirezionale, un insieme di argomenti che raramente si trova riunito in un unico corso.\u003C/span>\u003C/p>\n",{"title":842,"text":843},"È adatto se voglio lavorare con gli agenti AI e l'AI agentica?","\u003Cp class=\"font-size-body-1\">\u003Cspan class=\"text-color-grey-800\">Sì. MCP è uno dei mattoni fondamentali delle applicazioni agentiche moderne: saper costruire e integrare server MCP è una competenza sempre più richiesta a chi sviluppa agenti AI. Il corso ti dà proprio questo, con esercitazioni pratiche su strumenti reali e attuali.\u003C/span>\u003C/p>\n",[845,848,852,854],{"icon":846,"caption":71,"text":847},"icon-level","Da Beginner ad Advanced",{"icon":849,"caption":850,"text":851},"icon-round-check","PREREQUISITI","Nessun Prerequisito",{"icon":853,"caption":70,"text":54},"icon-calendar",{"icon":855,"caption":856,"text":857},"icon-lessons","LEZIONI","100% on demand",1783495937868]