Is MCP specific to Claude?

No — Anthropic introduced it, but it’s an open standard now stewarded by the Agentic AI Foundation (Linux Foundation), and it’s supported by ChatGPT, Cursor, Gemini, Microsoft Copilot, VS Code, and other clients, not just Claude.

Do I need to write code to use an MCP server?

No, as a user — connecting to one is usually pasting a URL into your AI client’s settings (or a short config-file entry for an IDE). Writing code is only needed if you’re BUILDING an MCP server yourself.

Is an MCP server the same as a plugin or an extension?

Conceptually similar (it extends what an AI assistant can do), but standardized — the same server works across any MCP-capable client, instead of needing a separate plugin per AI product.

What is an MCP server, and what is it used for?

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By The SkedCast Team · Updated 23 September 2026 · 5 min read

Key takeaways

MCP is an open standard (originally from Anthropic, now stewarded by the Agentic AI Foundation, a Linux Foundation project) for connecting AI assistants to external tools and data.
An MCP server exposes three kinds of things: tools (actions it can take), resources (data it can read), and prompts (reusable templates).
It uses a client-server architecture: your AI app is the client, the service (e.g. SkedCast) runs the server.
Adoption is broad — Claude, ChatGPT, Cursor, VS Code/Copilot, and others all support connecting to MCP servers today.

The problem MCP solves

Before a shared standard, every AI assistant needed its own bespoke integration format for every external service — a Claude plugin looked nothing like a ChatGPT plugin, which looked nothing like a Cursor extension. MCP standardizes the wire protocol so one server implementation can be used by any MCP-capable client, often described as "a USB-C port for AI" — one connector shape, many devices on either end.

The three primitives

Tools — executable functions the model can call to take an action (e.g. create_post, get_analytics_overview).
Resources — file-like structured data the model can read (e.g. a document, a dataset).
Prompts — predefined templates that guide how the client should use the server.

Client-server architecture

An MCP server is the side that exposes functionality — a company runs it against its own service (SkedCast runs one against its own API). An MCP client is the AI application that connects to one or more servers — Claude, ChatGPT, an IDE’s agent mode. A server can run locally (stdio, for tools that only need to touch your own machine) or remotely (HTTP, for a hosted service like SkedCast’s), and a client can connect to several servers at once.

Where the protocol stands today

Anthropic introduced MCP and has since donated it to the Agentic AI Foundation, a directed fund under the Linux Foundation co-founded by Anthropic, Block, and OpenAI — a deliberate move toward vendor-neutral governance as adoption grew past Anthropic’s own products. Support now spans ChatGPT, Cursor, Gemini, Microsoft Copilot, VS Code, and a large and growing number of public MCP servers.

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FAQ

Is MCP specific to Claude?: No — Anthropic introduced it, but it’s an open standard now stewarded by the Agentic AI Foundation (Linux Foundation), and it’s supported by ChatGPT, Cursor, Gemini, Microsoft Copilot, VS Code, and other clients, not just Claude.
Do I need to write code to use an MCP server?: No, as a user — connecting to one is usually pasting a URL into your AI client’s settings (or a short config-file entry for an IDE). Writing code is only needed if you’re BUILDING an MCP server yourself.
Is an MCP server the same as a plugin or an extension?: Conceptually similar (it extends what an AI assistant can do), but standardized — the same server works across any MCP-capable client, instead of needing a separate plugin per AI product.