Technology & AI
Radzivon Alkhovik
Jun 24, 2026
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Updated on
Jun 24, 2026
You ask ChatGPT to go through the outcomes of a meeting — but it has no access to the recording. You ask Claude to draft an email based on CRM data — but it can't see the CRM. Every time, you have to manually copy context into the chat. MCP solves exactly this problem.
MCP (Model Context Protocol) is an open protocol that allows AI agents to connect directly to external data sources and tools. One standard instead of dozens of different integrations. In this article, we'll break down how MCP works, which tools support it, and why it matters in a work context.
What MCP Is and What Problem It Solves
Before MCP, every AI tool integrated with external services in its own way. Want to give Claude access to files — one approach. Want to connect ChatGPT to a database — another. Cursor, Windsurf, custom agents — each had its own logic. Developers had to write separate integrations for every "agent + data source" pair.
MCP changes this: instead of N × M integrations — one standard protocol. A data source implements an MCP server once, and any MCP-compatible AI agent can connect to it.
Model Context Protocol as the Standard for AI Integrations
MCP was developed by Anthropic and published as an open standard in November 2024. The protocol defines how an AI agent requests data from external sources, how the source responds, and how tools (functions the agent can invoke) are passed.
MCP is often compared to USB-C for AI integrations. USB-C is a universal device connection standard — one port works with any compatible device. MCP is a universal standard for connecting AI agents to data — one MCP server works with any compatible agent.
How MCP Differs from a Direct API
Both MCP and APIs let programs retrieve data from external sources. The difference is who they're designed for.
An API is built for programs written by a developer. To use an API, you need to write code: form a request, handle the response, integrate it into the app's logic.
MCP is built for AI agents. The agent determines what data it needs, forms a request to the MCP server, and uses the response to complete the task. The user simply writes to the agent in natural language — no code required.
Parameter | REST API | MCP |
Who makes requests | A program (developer's code) | An AI agent |
Code required to use | Yes | No (for the end user) |
Interaction format | HTTP requests | Standardized MCP protocol |
Request flexibility | Fixed endpoints | Agent decides what to request |
Where it runs | Anywhere | Desktop applications only |
Who it's for | Developers | All AI agent users |
MCP doesn't replace APIs — it builds on top of them. The MCP server calls the data source's API itself and passes the result to the agent in a standardized format.
How MCP Works: Three Protocol Components
The MCP architecture consists of three elements that interact with one another. Understanding this structure helps clarify what actually happens when an AI agent retrieves data through MCP.
MCP Host — the Application Running the AI Agent
The MCP Host is the application where the AI agent runs. It initiates connections to MCP servers and manages access to them.
Examples of MCP Hosts:
Claude Desktop — Anthropic's desktop application, the first and most complete MCP Host
ChatGPT Desktop — MCP support added in 2025
Cursor — AI code editor with native MCP integration
Windsurf — AI editor by Codeium
Cline, Continue — popular AI extensions for VS Code
Important: MCP only works in desktop applications. The web versions of Claude (claude.ai) and ChatGPT (chatgpt.com) do not support MCP.
MCP Client — the Intermediary Inside the Agent
The MCP Client is a component inside the MCP Host that manages the connection to a specific MCP server. Each MCP Host can maintain multiple MCP Clients simultaneously — one per connected data source.
Users don't interact with the MCP Client directly. It's an internal architectural component that provides a standardized connection between the agent and the server.
MCP Server — the Source of Data or Tools
The MCP Server is a program that gives an AI agent access to data or functions. Each MCP server specializes in a specific source: a file system, a database, a service API, a web browser.
An MCP server can provide three types of capabilities:
Resources — data the agent can read: files, database records, documents, meeting transcripts
Tools — actions the agent can perform: send an email, create a task, write data
Prompts — ready-made instructions for common tasks
One MCP server typically combines several types. For example, the mymeet.ai MCP server provides meeting data (Resources) and tools for working with that data (Tools).
Which Tools Support MCP in 2026
MCP quickly became the standard for AI agents. Within the first six months of its release, most major AI tools added support.
AI Agents with MCP Support
On the agent side, MCP is supported by:
Claude Desktop — the first and most complete MCP Host from Anthropic
ChatGPT Desktop — MCP support arrived in 2025
Cursor — AI code editor with native MCP integration
Windsurf — AI editor from Codeium
Cline, Continue — popular AI extensions for VS Code
Zed — code editor with MCP support
The list keeps growing — as an open standard, MCP is being adopted by new tools continuously.
Ready-Made MCP Servers: Categories and Examples
On the data source side, hundreds of ready-made MCP servers exist. A few categories:
File system and local data: access to files and folders on your computer
Databases: PostgreSQL, SQLite, MongoDB
Development tools: GitHub, GitLab, Jira, Linear
Communications: Slack, Gmail, Google Calendar
Browser: tab management, page reading
AI services and products: meetings, documents, CRM
mymeet.ai falls into the last category — it gives AI agents access to online meeting data through the MCP protocol.
How to Connect an MCP Server to Claude or ChatGPT
Connecting an MCP server to an AI agent takes a few minutes. The process is the same across most MCP Hosts.
What You Need to Connect an MCP Server
To work with MCP, you'll need:
a desktop application with MCP support (Claude Desktop, ChatGPT Desktop, Cursor)
an API key for the service the MCP server connects to
a configuration file (JSON) with the server settings
The config typically contains the MCP server's address, the command to launch it, and authorization parameters. Most services provide a ready-made config to copy directly.
The General Process for Connecting an MCP Server
The connection process is the same across most MCP Hosts:
Get the service's API key from your account settings
Copy the ready-made MCP server config from the service's documentation
Paste the config into the MCP settings in the desktop application
Restart the application
After that, the AI agent can see the connected MCP server and query its data when answering questions. The user interacts with the agent as usual — in natural language.
Mymeet.ai as an MCP Server: Meetings in Your AI Agent's Context
Mymeet.ai — a service for recording, transcribing, and analyzing online meetings — implements an MCP server that gives AI agents access to meeting data. Once connected, ChatGPT, Claude, or Cursor "know" about your meetings and can answer questions about them.
What an AI Agent Gets Through the mymeet.ai MCP Server
Through the mymeet.ai MCP server, an AI agent gains access to:
meeting transcripts with speaker breakdown and timestamps
AI summaries and brief overviews of each meeting
participant lists and meeting duration
tasks and decisions extracted by AI
workspace metadata
This makes it possible to ask the agent questions in natural language: "what did the team discuss last week," "what tasks were assigned at Tuesday's sync," "what did the client say about the budget on the last three calls."
How to Connect mymeet.ai via MCP
✅ Get your API key independently in Settings → API Key — no requests or waiting required
✅ Ready-made connection cards for Claude, ChatGPT, Cursor, and other agents — in the Integrations → AI Agents section
✅ Each card includes a config to copy and a step-by-step setup guide
✅ One key works with any number of MCP-compatible applications
✅ Mymeet.ai MCP works in desktop applications
✅ Available on Lite, Pro, and Business plans. On the free plan, integration cards and guides are accessible for exploration
Summary: Why MCP Matters and What It Changes
MCP solves one specific problem: it gives AI agents access to up-to-date data from external sources — without writing code and without manual copying. The user connects an MCP server once — and the AI agent starts working with real data, not just what it was told in the chat.
For businesses, this means meetings, documents, CRM data, and other sources become part of the AI agent's context. Instead of "explain this based on the transcript I'm pasting" — simply "what did we discuss" — the agent knows where to find the data on its own.
MCP is a young standard, but it has already become the de facto way to connect AI agents to external data. The sooner you configure the MCP servers you need, the sooner AI agents become genuinely useful tools in real work — not just chatbots with limited context.
Frequently Asked Questions About MCP
What is MCP (Model Context Protocol)?
MCP (Model Context Protocol) is an open protocol developed by Anthropic that allows AI agents to connect to external data sources and tools using a single standard. Instead of building a separate integration for every "agent + data source" pair, MCP provides one universal connection method.
How is MCP different from an API?
An API is built for programs that developers write. MCP is built for AI agents — they decide for themselves what data to request. End users don't need to write any code: connecting an MCP server is done through the settings of a desktop application.
What is an MCP server?
An MCP server is a program that gives an AI agent access to a specific data source or set of tools. Each MCP server specializes in its own source: a file system, a database, a service (such as mymeet.ai). The agent connects the MCP servers it needs and gains access to their data.
Which AI agents support MCP?
Claude Desktop, ChatGPT Desktop, Cursor, Windsurf, Cline, Continue (VS Code extensions), and Zed. The list is growing — MCP has been adopted as a standard by most major AI tools.
Does MCP work in the browser versions of Claude or ChatGPT?
No. MCP only works in desktop applications. The web versions at claude.ai and chatgpt.com do not support MCP. To use MCP, you need to install a desktop application — Claude Desktop or ChatGPT Desktop.
Do you need programming skills to use MCP?
For end users — no. Connecting an MCP server comes down to copying a config from the service's documentation and pasting it into the agent's settings. Building a new MCP server from scratch requires programming, but using existing ready-made servers does not.
What is an MCP Host?
An MCP Host is a desktop application with an AI agent that manages connections to MCP servers. Claude Desktop, ChatGPT Desktop, and Cursor are examples of MCP Hosts. The MCP servers the agent can query are specified in the Host's settings.
How many MCP servers can be connected at once?
There's no limit on the number of connected MCP servers. An agent can simultaneously work with a file system, a database, a meeting service, and email — all connected as separate MCP servers in the application's settings.
Is it safe to give an AI agent access to data through MCP?
Security depends on the specific MCP server and its configuration. The API key used to access your data is stored in a config file on your own computer. The agent only receives the data that the MCP server provides — and only within the permissions of your account. If a key is compromised, it can be regenerated in the service's settings.
Where can I find ready-made MCP servers?
Anthropic publishes an official MCP server repository on GitHub. Major services publish their own MCP servers in their "Integrations" or "Developers" sections. mymeet.ai provides ready-made connection cards for each supported AI agent in the Integrations → AI Agents section.
Radzivon Alkhovik
Jun 24, 2026
