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MCP: The Universal Tool Layer

🔧 Tool Use & Function Calling⏱ 12 min⭐ 80 BASE XP⌨ HANDS-ON LAB

Model Context Protocol (MCP)

MCP is the open standard for connecting AI to data sources and tools. Think of it as USB-C for AI.

Instead of writing custom API wrappers for every service, you run an MCP Server. The MCP Server exposes standard Tools, Resources (read-only data), and Prompts.

  • MCP Servers: Lightweight connectors to databases, Jira, GitHub, local files, etc.
  • MCP Clients: Applications like Claude Desktop, Cursor, or your custom agent framework that consume the server.
  • Transports: Connect via local stdio for same-machine servers or remote Streamable HTTP for stateless, network-accessible servers. Streamable HTTP replaced the earlier SSE transport with a simpler, stateless protocol design that eliminates the need for long-lived connections and server-side session management.
💡 Key Insight: MCP separates the "thinking" (the LLM) from the "doing" (the tools). Because it is a unified protocol, you can hot-swap any compatible agent client with any compatible tool server.
⌨ HANDS-ON LABLaunch an MCP Server Locally
⭐ +150 XP

Before wiring MCP into an agent, prove the plumbing works. Launch a reference server, then open the MCP Inspector to poke at its tools.

1Launch the filesystem reference server with npx (package: @modelcontextprotocol/server-filesystem).
2Open the MCP Inspector to interactively test any server (package: @modelcontextprotocol/inspector).
lab-sandbox — simulated environment
INFINITY LAB SANDBOX v2.6 — simulated shell
Type the command for the current objective. Helpers: "hint", "solution", "clear".
$
OBJECTIVE 1 / 2 — type "hint" if stuck
SYNAPSE VERIFICATION
QUERY 1 // 2
What are the three primary capabilities exposed by an MCP server?
Databases, APIs, Local Files
Tools, Resources, Prompts
Authentication, Routing, Execution
Agents, LLMs, Memory
MCP: The Universal Tool Layer Tutorial | Tool Use & Function Calling — AI Agents Academy