What is MCP?

TL;DR

MCP, the Model Context Protocol, is an open standard for connecting AI assistants to outside tools and data. A service publishes an MCP server describing what it can do, and any MCP-compatible client can call it without custom glue code. Anthropic released it in November 2024 and it has since been adopted by Claude, Cursor, Windsurf, VS Code and others. For web data, it means an assistant can fetch a live page as a normal part of a conversation rather than through a bespoke integration.

The problem it solves

Before MCP, every pairing of an assistant and a tool needed its own integration. Ten assistants and ten tools meant a hundred separate pieces of work, each with its own auth handling, schema format and failure modes. Nobody built most of them, so assistants stayed cut off from the systems people actually use.

MCP inverts that. A tool describes itself once, in a standard shape, and any client that speaks the protocol can use it. The same server works in Claude Code, Cursor and a custom agent you wrote yourself.

What an MCP server exposes

Three things, and the distinction matters when you are choosing between servers:

• Tools. Functions the model can call, each with a name, a description and a typed schema for its arguments. This is the part most people mean when they say MCP.
• Resources. Data the client can read, addressed by URI. Closer to a file than a function call.
• Prompts. Reusable templates a user can invoke deliberately, often surfaced as slash commands.

A server is only as good as its tool descriptions. The model picks a tool by reading its description, so a vague one gets ignored or misused regardless of how well the underlying service works.

Where Zenrows fits

The Zenrows MCP server gives any MCP-compatible client access to the live web, including pages behind anti-bot protection. Scraping and browser automation arrive as tools the assistant can call directly, so an agent can read a page that would return a block page to a plain HTTP request. The server is hosted, so a client can point at it directly with your API key, and the Zenrows CLI can do the wiring for you if you would rather not edit config by hand. Either way the same server works across Claude Code, Cursor, Windsurf, VS Code and the rest.

Key takeaways

MCP is a standard interface between AI assistants and external systems, replacing per-pair integrations with one server that every compatible client can use. It carries tools, resources and prompts. For web data specifically, it is what lets an assistant read a live page mid-conversation instead of relying on whatever was in its training data.