The short version
The Model Context Protocol, or MCP, is an open standard for connecting AI assistants to other software. It defines a common way for an assistant to discover what a system can do and to use it. A system that speaks MCP is called an MCP server. The app where you talk to the AI, such as Claude Desktop, Claude Code or another assistant, is the MCP client.
Before MCP, every connection between an AI app and a business tool was built by hand, in a different way each time. MCP gives everyone the same plug shape. A server built once can be used by many assistants, and an assistant can use many servers.
How it works
An MCP server describes a set of tools. Each tool has a name, a short description and the inputs it needs. A CRM server might offer tools such as "search contacts", "get deal" and "create task". When you ask the assistant a question, it reads the list of available tools, decides which ones help, calls them and uses the results in its answer.
Servers can also offer resources, such as documents the assistant can read, and prompts, which are ready-made instructions for common tasks. Some servers run on your own computer and talk to the assistant directly. Others are hosted by the vendor and reached over the internet, usually with a sign-in through your existing account.
The protocol keeps evolving. The specification dated July 28, 2026 made the core of the protocol stateless, which makes hosted servers simpler to run and scale. For a business, the practical effect is that more vendors can offer reliable hosted servers.
Where it came from and who supports it
Anthropic introduced MCP in November 2024. OpenAI adopted it in March 2025 and Google DeepMind in April 2025. In December 2025, Anthropic donated MCP to the Agentic AI Foundation, a directed fund under the Linux Foundation co-founded by Anthropic, Block and OpenAI. The protocol is now developed in the open through working groups and a formal proposal process.
That broad support matters. It means an investment in MCP servers for your systems is not tied to one AI provider. You can switch assistants or use several without rebuilding the connections.
Why it matters for a business
AI is most useful when it can see your real data and act in your real tools. A general assistant can write a polite email. An assistant connected to your CRM, calendar and help desk can write the right email, to the right customer, with the right details, and book the follow-up.
- Less copying and pasting. Staff ask questions in plain English instead of switching between systems.
- Faster answers. "Which invoices are overdue for our top ten customers?" becomes a question, not a report request.
- Reusable connections. One server for your system can serve many assistants and workflows.
- Agents that do real work. AI agents use MCP servers as their hands: looking things up, updating records and triggering actions.
Everyday examples
A sales rep asks the assistant to summarize everything about an account before a call. The assistant uses the HubSpot server to read the contact and deal history and the Gmail server to find the last emails.
A finance assistant checks which invoices are unpaid through the Stripe server and drafts polite reminders for a person to approve. An operations manager asks for last week's bookings from a database server connected to a read-only replica.
A developer asks a coding assistant to look at an error in Sentry, find the related code on GitHub and propose a fix for review.
Risks and how to manage them
Connecting AI to business systems gives it real power, so treat each server like a new employee with a key to part of the office.
- Least access. Give each server only the permissions it needs. Start read-only.
- Trusted sources. Prefer official servers from the vendor or the MCP project. Review community servers before use.
- Untrusted content. Web pages, emails and documents can contain text written to trick an AI. Treat content as data, not instructions.
- People approve actions. Require approval for anything that sends messages to customers, changes records in bulk or moves money.
- Logs. Keep a record of which tools were called, with what inputs, by whom.
How to get started
Pick one task that wastes time every week and involves one or two systems. Find the official server for those systems in our MCP server directory, connect it read-only in a test setup and try real questions. When the answers are reliable, add the actions you need, with approval steps.
If your key system has no MCP server, one can be built on top of its API. That is often a small project, and it makes the system available to every AI assistant your team uses. See MCP integration and API integration.