Before MCP, connecting an AI assistant to your own tools meant writing custom integration code for every single tool, every single time — one connector for Slack, a different one for GitHub, another for your database. The Model Context Protocol changes that math: build one MCP server for a tool, and every MCP-compatible AI application can use it without custom glue code. It’s become common enough by late 2026 that it’s described as the “USB-C for AI” — one standard connector instead of a different cable for every device.
What MCP Actually Is
MCP (Model Context Protocol) is an open standard, introduced by Anthropic in November 2024, for connecting AI applications to external data sources, tools, and workflows. Instead of an AI model being limited to whatever training data it saw, MCP gives it a standardized way to read local files, query a database, call an API, or trigger a workflow — live, at the moment it’s asked to.
The protocol defines three roles:
- MCP Host — the AI application itself (Claude, an IDE like Cursor, a custom agent) that needs access to outside tools or data.
- MCP Client — a connector the host creates for each server it talks to, handling the actual protocol communication.
- MCP Server — a lightweight program that exposes a specific tool or data source (a GitHub repo, a Postgres database, a Figma file) in the standard MCP format.
A host can connect to many servers at once, each handling one specific capability. That’s the actual value: the AI application doesn’t need to know anything special about GitHub versus Slack versus your internal API — it talks to all of them the same standardized way.
Why It Took Off
By Q2 2026, the community-built MCP server ecosystem had grown past 200 tools — GitHub, Slack, PostgreSQL, Stripe, Figma, Docker, and Kubernetes among the most widely used. That growth is a direct consequence of the standard doing one thing well: a developer builds an MCP server for their tool once, and it works with any MCP-compatible AI application, not just one vendor’s product. That’s a very different economics than building a custom plugin per AI platform.
A Simple Example
Say you want Claude to be able to check your team’s GitHub issues. Without MCP, that means writing custom code specifically wiring Claude’s API to GitHub’s API, handling auth, parsing responses — a one-off integration. With MCP, you (or someone else) built a GitHub MCP server once. Point any MCP-compatible AI application at it, and it can read issues, open pull requests, or check CI status — using the same standard interface it uses for every other MCP server it’s connected to.
Frequently Asked Questions
Is MCP the same as a plugin or a function call?
Related, but more general. A single function call is one specific action; an MCP server can expose many tools, resources, and prompts at once, and any MCP-compatible host can discover and use all of them without custom per-tool integration code.
Who created MCP and is it open?
Anthropic introduced MCP in November 2024 as an open standard, not a proprietary Anthropic-only feature. That openness is a big part of why a community ecosystem of 200+ servers has formed around it.
Do I need to know MCP to just use Claude or ChatGPT normally?
No — MCP matters when you (or a tool you use) wants to connect an AI application to a specific external system. Casual chat use doesn’t require knowing anything about it.
Conclusion
MCP solves a real, boring, expensive problem: every AI-to-tool integration used to be its own one-off project. Standardizing that connection is why the ecosystem grew as fast as it did. If you’re building anything that needs an AI application to reach outside its own training data — your files, your APIs, your internal tools — MCP is very likely already the right way to do it rather than a custom integration. The next guide in this series walks through building an actual MCP server step by step.
Sources: Anthropic, Introducing the Model Context Protocol; Model Context Protocol official documentation.
📑 About the author: I also build Digital Bizz Card — hosted digital business cards you can share with a QR code, no app required.
