MCP guide – something I came across months ago (composio.dev)

Model Context Protocol (MCP) is an open, client-server protocol that standardizes how applications expose context, tools and data to LLMs so agents can perform real-world, multi-step workflows reliably. Instead of stuffing logic into brittle prompts or bespoke function-calls for each app, MCP servers expose capabilities (tools), data (resources identified by URIs like file:/// or postgres://), and reusable prompts over a JSON‑RPC interface. MCP clients (e.g., Cursor, Claude Desktop) request available capabilities, present them to the model, relay tool invocations back to servers, and handle auth, letting an LLM say “reschedule meetings with Alice” and then use list-events → edit-resource → update-events-from-resource in a controlled sequence. Technically, MCP separates concerns across three layers—Model↔Context (instructions and working memory), Context↔Protocol (structured state and step handling), Protocol↔Tools (standardized action APIs)—so models remain the “thinker” and tools the “doers.” That reduces hallucinations, enables durable multi-step chains and cross-vendor portability (swap GPT, Claude or Gemini without rewriting all integrations). Practical implications: one AI can plug into thousands of apps (Gmail, Notion, Slack, Salesforce) if MCP servers exist, enabling more reliable agent automation. It’s not a silver bullet—MCP requires server implementations per service, careful auth/security design, and the protocol is still evolving—but it’s a major step toward scalable, maintainable AI agents that actually get things done.