MCP Academy is the premier free interactive learning platform by Infinity Tech Stack for Anthropic's Model Context Protocol (MCP), now governed by the Linux Foundation. It features 13 modules, 48 lessons, 48 hands-on terminal labs, and 140 quizzes covering MCP servers, clients, tools, Streamable HTTP, OAuth 2.1, and the 2026-07-28 stateless specification with zero sign-up required.

How is Infinity MCP Academy different from official Model Context Protocol documentation?

While modelcontextprotocol.io provides the core technical specifications and basic SDK quickstarts, Infinity Tech Stack's MCP Academy is an independent, 100% free interactive curriculum with 13 modules, 48 lessons, 48 in-browser terminal labs, and 140 quizzes. It teaches real-world server and client development, Streamable HTTP, OAuth 2.1, the 2026-07-28 stateless core specification, multi-server gateways, and enterprise security with zero sign-up required.

How long does MCP Academy take to complete?

MCP Academy contains approximately 4 to 5 hours of interactive training across 13 modules and 48 lessons. Progress is saved locally in your browser so you can learn at your own pace.

Is the MCP Academy free?

Yes. The MCP Academy is free to access, with modules, lessons, quizzes, and labs available without sign-up.

What is the Model Context Protocol (MCP)?

MCP is an open standard (now governed by the Linux Foundation) that provides a universal way for AI models and agents to connect to tools, data sources, and external systems. Think of it as USB-C for AI.

What topics does the MCP Academy cover?

The course covers MCP architecture, server/client development, tools & function calling, resources & prompts, transport layers (stdio, Streamable HTTP), OAuth 2.1 security, production deployment, MCP Gateways & Proxies, Linux Foundation governance, enterprise audit logging, multimodal/audio content, client SDK development, MCP Inspector debugging, integration testing, the official MCP Registry, and real-world case studies from DevOps, CRM, and AI coding assistant deployments.

What is an MCP Gateway?

An MCP Gateway sits between AI clients and multiple MCP servers, providing semantic routing, tool aggregation, token optimization, and centralized observability - similar to an API gateway but for the MCP protocol.

Do I need programming experience?

Basic familiarity with JSON and APIs is helpful but not required. The course starts from fundamentals and builds progressively to advanced production patterns, including hands-on server building tutorials.

How do I debug MCP servers?

The course teaches you to use the MCP Inspector (an official interactive debugging tool), write automated integration tests using the Client SDK, and diagnose common issues like stdout corruption and capability negotiation failures.

Does the MCP Academy include hands-on labs?

Yes. Hands-on terminal labs are embedded in relevant lessons, including objectives, hints, solution commands, and XP rewards.

What is the latest version of MCP?

The current MCP specification revision is 2026-07-28, which shipped after its Release Candidate and made the protocol fully stateless - removing the initialize handshake and protocol-level sessions entirely, adding a mandatory server/discover RPC, and moving Tasks out of the core spec into an official extension. The previous 2025-11-25 revision introduced experimental Tasks, URL-mode elicitation, tool calling in sampling, icon metadata for tools and resources, OpenID Connect Discovery, OAuth Client ID Metadata Documents, and JSON Schema 2020-12 as the default dialect.

MCP Tasks (originally introduced experimentally as SEP-1686 in 2025-11-25 and formalized in 2026-07-28 as the official io.modelcontextprotocol/tasks extension) support long-running, durable operations. Instead of blocking on a single HTTP request, a server returns a task handle that the client polls via tasks/get or updates via tasks/update - essential for agent workflows that run for minutes or hours.

What is the difference between MCP and function calling?

Function calling lets a single model invoke functions you define inline for that one app. MCP is an open, transport-based standard that exposes tools, resources, and prompts from independent servers to any compatible client - so one MCP server works across Claude, ChatGPT, Cursor, and VS Code without rewriting integrations.

How do I build an MCP server?

Scaffold a server with the official Python or TypeScript SDK, register tools (functions), resources (data), and prompts, then expose it over stdio for local use or Streamable HTTP for remote use. The MCP Academy includes hands-on labs that build, connect, and inspect a real server step by step.

What is the best MCP course?

The MCP Academy is a free, interactive course with 13 modules, 48 lessons, 48 hands-on terminal labs, and 140 quiz questions - covering everything from MCP architecture to production security, gateways, the official MCP Registry, and the latest 2026-07-28 stable spec. Progress saves locally with no sign-up required.

What problem does MCP primarily solve?

Standardizing AI integration to external data sources and tools — MCP standardizes how AI applications connect to external data sources and tools, replacing custom integrations.

In the MCP ecosystem, who dictates the security boundaries?

The MCP Server — The MCP Server defines precisely what tools, resources, and data are exposed, effectively controlling the security boundary.

What is MCP? — Foundation

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1. What is MCP?2. Core Architecture3. Host vs Client vs Server

What is MCP?

📚 Foundation⏱ 5 min⭐ 50 XP⌨ Hands-on lab

The Universal Standard for AI

The Model Context Protocol (MCP) is an open standard that enables AI models to securely connect to local and remote data sources, and perform actions.

Historically, every AI application needed custom point-to-point integrations for every data source (GitHub, Slack, Jira, local files). MCP standardizes this connection. Once an MCP server is written, any MCP-compatible AI client (like Claude Desktop or Cursor) can immediately use it.

💡 Key Insight: MCP is often called the "USB-C of AI." It separates the AI client from the data/tools, creating a unified plug-and-play ecosystem.

🌐 Open Industry Governance: Originally developed and open-sourced by Anthropic, the Model Context Protocol transitioned to neutral, open governance under the Linux Foundation's Agentic AI Foundation (AAIF), ensuring vendor-neutral standardization supported across Anthropic, Google, Microsoft, OpenAI, and the broader open-source ecosystem.

Why Does This Matter?

No more siloed data: AI can finally access your local databases, intranet, and private code securely.
Security boundaries: The MCP server controls exactly what the AI can see and do. The AI only sees what the server sends.
Write once, use everywhere: Build the integration once, and use it across all your AI assistants.

Specification Timeline & Official SDKs

Spec Version	Milestone
`2024-11-05`	Initial open-source release (stdio + legacy dual-endpoint HTTP+SSE)
`2025-03-26`	Introduced Streamable HTTP transport, OAuth 2.1 framework, and Tool Annotations
`2025-06-18`	Added `outputSchema` / `structuredContent`, Form-mode Elicitation, and RFC 8707 Resource Indicators
`2025-11-25`	Added experimental Tasks (SEP-1686), URL-mode Elicitation, Sampling with tools, OIDC Discovery, Client ID Metadata Documents, and JSON Schema 2020-12
`2026-07-28`	Current Stable Spec: Stateless Core (removed `initialize` & `Mcp-Session-Id`), mandatory `server/discover`, SEP-2243 HTTP routing headers, `subscriptions/listen`, MRTR, and `io.modelcontextprotocol/tasks` extension

Official Tier-1 & ecosystem SDKs under github.com/modelcontextprotocol include TypeScript (@modelcontextprotocol/server & @modelcontextprotocol/client in v2; @modelcontextprotocol/sdk in v1), Python (mcp / FastMCP), Go (go-sdk), Rust (rmcp), C#, Ruby, and Java (plus Kotlin, Swift, and PHP).

⌨ HANDS-ON LABInspect Reference Memory Server

⭐ +100 XP

Explore the MCP standard hands-on. Run the official reference memory server with npx.

1Launch the reference memory server using npx.

lab-sandbox — simulated environment

INFINITY LAB SANDBOX v2.6 — simulated shell
Type the command for the current objective. Helpers: "hint", "solution", "clear".
$

OBJECTIVE 1 / 1 — type "hint" if stuck

🧪 Knowledge Check

Press 1-4 to select1 of 3

What analogy is commonly used to describe the Model Context Protocol?

The blockchain of AI

The USB-C of AI

The SQL of AI

The Ethernet of AI