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What Is Model Context Protocol (MCP)?

The open standard that lets AI tools connect directly to your data sources like Evernote

Understanding Model Context Protocol

Model Context Protocol, commonly referred to as MCP, is an open standard created by Anthropic that defines how AI tools communicate with external data sources. Before MCP existed, every AI application that wanted to access your data in a specific service needed its own custom integration, which meant fragmented support and inconsistent behavior across tools. MCP solves this by providing a universal protocol that any AI tool can implement to connect to any compatible data source. Think of it like how USB standardized the way devices connect to computers. Instead of every device needing a proprietary cable, USB gave everyone a common plug. MCP does the same thing for AI-to-data connections, creating a shared language that both sides understand.

How MCP Works

MCP operates on a client-server architecture where the AI tool acts as the client and the data source runs a server. When you configure an AI assistant like Claude to connect to an MCP server, the assistant can send structured requests to read data from or write data to the connected service. The server receives these requests, processes them according to its own rules and your permissions, and returns the appropriate response. This communication happens through a well-defined set of operations that the protocol specifies, so both the client and server know exactly what to expect. The standardization means that a single MCP server can support many different AI clients without any modification, and a single AI client can connect to many different MCP servers simultaneously.

The Role of MCP Servers

An MCP server is the component that sits between the AI tool and the data source, translating protocol requests into actions on your data. Each service that wants to support MCP builds and maintains its own server implementation. For example, the Evernote MCP server handles requests related to reading and creating notes in your Evernote account. The server is responsible for authenticating your identity, ensuring the AI tool has the right permissions, and executing the requested operations against the underlying service. This design keeps the data source in control of how its data is accessed, while the AI tool simply speaks the standard MCP language to make its requests. Developers building MCP servers can choose exactly which capabilities to expose.

The Role of MCP Clients

On the other side of the connection, MCP clients are the AI tools that initiate requests to servers. Claude, Claude Code, Cursor, and Windsurf are all examples of applications that natively support MCP as clients. When you add an MCP server to your client configuration, the client discovers what capabilities the server offers and makes those available to you during your interactions. For instance, once Claude knows it can read your Evernote notes through the MCP server, it can offer to search your notes when you ask a question that might benefit from your stored knowledge. The client handles the user interface and the AI reasoning, while the MCP connection provides the data pipeline to your information.

Why MCP Was Created

The problem MCP addresses is straightforward but significant. AI assistants are powerful reasoners and writers, but they are limited by the information they can access. Without a connection to your personal or organizational data, an AI tool can only work with what you paste into the conversation or what it finds on the public web. MCP was created to close this gap by giving AI tools a standardized way to tap into the data sources where your real information lives. Anthropic developed and open-standardd the protocol because a standard benefits everyone. Data sources only need to build one server, AI tools only need to implement one client protocol, and users get seamless connections between the tools they already use without waiting for bespoke integrations to be built.

MCP and Evernote

Evernote is building an MCP server that brings the protocol's benefits directly to its users. The Evernote MCP server supports two capabilities: Read, which allows AI tools to access and retrieve your existing notes, and Create, which enables AI tools to save new notes into your account. This means that when you use an MCP-compatible tool like Claude, you can ask it to find information across your note library, summarize documents, or compile research from your notes. You can also have the AI save its output back to Evernote as a new note, keeping everything organized in one place. The MCP server is currently in development, and users can join a waitlist to be notified when it launches. Evernote already offers built-in AI features like AI Note Cleanup, AI Edit, and Semantic Search, and the MCP server extends these by connecting your notes to external AI tools.

The Broader MCP Ecosystem

MCP is not limited to any single AI tool or data source. Because it is an open standard, any developer can build an MCP server for their service, and any AI application can add MCP client support. This creates a growing ecosystem where new connections become available without requiring coordination between every pair of tools and services. As more services adopt MCP, the value of each individual server grows because it instantly works with every compatible client. For Evernote users, this means that as new AI tools add MCP support, those tools will be able to connect to your notes through the same Evernote MCP server without any additional setup on your part. The ecosystem effect makes MCP increasingly useful over time as adoption spreads across both AI tools and data services.

Getting Started with MCP

If you want to start using MCP with your Evernote notes, the first step is to join the waitlist for the Evernote MCP server. Once available, you will configure your preferred AI tool to connect to the server by adding the server details to your tool's MCP configuration. Most MCP-compatible tools like Claude Desktop make this process accessible through a configuration file where you specify server endpoints and authorization details. You do not need to be a developer to set up these connections, although developers will appreciate the flexibility to customize their setup. In the meantime, you can explore Evernote's existing AI features within the app, including the AI Assistant, which provides intelligent interaction with your notes directly inside Evernote without requiring any external configuration.

The Future of AI and Data Connectivity

Model Context Protocol represents a broader shift in how AI tools interact with the data that matters to users. Rather than keeping AI assistants siloed from your personal and professional information, MCP creates bridges that let AI reason over your actual data. For Evernote users, this means the notes you have been collecting and organizing for years become a live resource that AI tools can draw upon in real time. As the MCP ecosystem grows and more services build servers, the value of each connection multiplies because AI tools gain a richer understanding of your context across multiple data sources. The open nature of the standard ensures that this growth benefits everyone equally, rather than favoring any single platform or vendor in the AI landscape.

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Frequently Asked Questions

MCP stands for Model Context Protocol. It is an open standard created by Anthropic that defines how AI tools connect to and communicate with external data sources. The protocol provides a structured way for AI assistants to request information from services like Evernote, databases, and other tools without each integration needing to be built from scratch.

Model Context Protocol was created by Anthropic, the company behind the Claude AI assistant. Anthropic developed MCP as an open standard, which means it is freely available for any developer or company to implement. The open nature of the protocol encourages broad adoption across the AI ecosystem, benefiting both AI tool makers and data source providers equally.

MCP uses a client-server architecture. The AI tool acts as an MCP client, and the data source runs an MCP server. When you configure the connection, the AI client can send structured requests to the server to read or write data. The server processes these requests against your account and returns the results. This standardized communication means any MCP client can talk to any MCP server without custom integration work.

Several AI tools natively support MCP as clients. Claude and Claude Code from Anthropic are primary MCP clients. AI-enhanced code editors including Cursor and Windsurf also support MCP connections. As the standard continues to gain adoption, more AI tools are adding MCP support, which means the number of compatible clients grows over time without requiring changes to existing MCP servers.

Yes, Evernote is building an MCP server that will allow compatible AI tools to connect to your note library. The server supports Read capabilities for accessing existing notes and Create capabilities for saving new notes. The Evernote MCP server is currently in development, and you can join the waitlist to be notified when it becomes available. This adds to Evernote's existing AI features like AI Note Cleanup and Semantic Search.

Yes, MCP is an open standard. Anthropic released the protocol specification publicly so that any developer or company can implement MCP in their tools and services. This open approach means that MCP is not controlled by a single vendor, and the ecosystem benefits from contributions and adoption across many different organizations. Being open is fundamental to MCP achieving its goal of standardizing AI-to-data connections.

Yes, most MCP-compatible AI tools provide straightforward configuration options that do not require programming knowledge. Setting up an MCP connection in tools like Claude Desktop typically involves specifying server details in a configuration file or settings interface. The process is similar to setting up any other software connection. While developers can build custom MCP integrations, everyday users can benefit from MCP through the tools they already use.

An MCP server is a software component that a data source runs to make its data accessible to AI tools through the Model Context Protocol. Each service builds its own MCP server that defines which operations are available, such as reading or creating data. The Evernote MCP server, for example, lets AI tools read your notes and create new ones. The server handles authorization and ensures that data access follows your permissions.

An MCP client is the AI tool side of an MCP connection. It is the application that sends requests to MCP servers to read or write data on your behalf. When you use Claude and it accesses your Evernote notes through MCP, Claude is acting as the MCP client. Clients discover what capabilities a server offers and use those capabilities during your interactions with the AI.

Yes, MCP is designed to support multiple simultaneous server connections from a single AI client. This means you could connect Claude to your Evernote notes, a file system server, and other MCP servers all at the same time. Each connection operates independently, and the AI tool can draw on data from all connected servers when responding to your requests. This multi-server capability is one of the key advantages of the standardized protocol approach.

While both MCP and traditional APIs enable software to communicate with data sources, MCP is specifically designed for AI tool interactions. Traditional APIs require developers to write code for each integration, whereas MCP provides a standard protocol that AI tools already understand. An AI client that supports MCP can connect to any MCP server without custom development. MCP also includes conventions for capability discovery, meaning the AI tool can automatically learn what operations a server supports.

Yes, MCP connections operate with your explicit permission. When you set up an MCP server connection, you authorize with your account and define the scope of access. The MCP server enforces these permissions, so the AI tool can only access the data you have authorized. You remain in control of the connection and can revoke access at any time by removing the server configuration from your AI tool.

The MCP ecosystem is growing as more services and AI tools recognize the value of standardized connections. Because MCP is an open standard, any service can build a server without needing permission from Anthropic or any other organization. The network effect of MCP means that each new server makes the protocol more valuable for existing clients, and each new client makes existing servers more useful. This dynamic encourages continued adoption across the industry.

MCP server connections depend on the AI client application you are using. If the AI tool you use on your mobile device supports MCP connections, then it can communicate with MCP servers like the Evernote server. The protocol itself is not limited to any platform, but the availability of MCP features depends on the specific client application and whether it has implemented MCP support on its mobile version.

MCP servers are designed to handle requests efficiently regardless of library size. The protocol supports targeted queries, so when an AI tool asks for specific notes or searches for particular content, the server processes the request against your full library and returns only the relevant results. You do not need to worry about the size of your Evernote library affecting the MCP connection, as the server manages data retrieval on its end.

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