What Exactly is Model Context Protocol (MCP)?
The Model Context Protocol (MCP) acts as a universal intermediary, facilitating seamless communication between Large Language Models (LLMs) and a diverse array of external resources. It establishes a standardized framework that empowers LLMs to intelligently identify and utilize available resources effectively. This enables the LLM to determine when and why it should leverage these resources to execute tasks, augment its knowledge base, or enhance its overall comprehension.
The range of external data accessible via MCP is remarkably broad, encompassing local file systems, structured databases, Application Programming Interfaces (APIs), Software-as-a-Service (SaaS) applications, and numerous other sources. It provides a flexible and adaptable architecture for integrating diverse data sources with LLMs.
Fundamentally, MCP equips LLMs with the ability to make deterministic requests for specific data or actions. This allows them to draw upon information that resides beyond their pre-existing training datasets, providing them with the means to formulate more accurate, comprehensive, and contextually relevant responses. This is especially useful in cases where the LLM’s internal knowledge is insufficient or outdated.
The widespread adoption of MCP is rapidly reshaping the landscape of AI, with a multitude of AI companies actively integrating it into their respective platforms. This demonstrates the industry’s recognition of MCP’s potential to revolutionize the way AI systems interact with and utilize external data.
Why the Surge in MCP Interest?
The primary driver behind MCP’s burgeoning popularity is its ability to standardize the process of connecting external data sources to LLMs. This standardization offers developers a compelling advantage: the ability to create a single integration for an LLM and seamlessly deploy it across a wide range of tools and LLMs that adhere to the MCP standard. This ‘write once, use everywhere’ paradigm dramatically simplifies the integration process, reducing the time, cost, and complexity associated with connecting LLMs to external data.
Moreover, the emergence of ‘app stores’ and ‘marketplaces’ that feature MCP servers is further streamlining the integration process. These marketplaces offer developers a curated selection of pre-built MCP servers that can be rapidly incorporated into their development environments. In addition, dedicated service providers are emerging that specialize in the creation of custom MCP servers, catering to highly specific needs and requirements. This further reduces the barrier to entry for organizations looking to leverage the power of MCP.
Is This the First Instance of LLMs Interacting with External Data?
The concept of Agentic AI, characterized by its capacity to operate autonomously and interact with external sources, has been in development for a considerable period of time. However, previous implementations were often idiosyncratic, meaning that each tool required a unique, custom integration. This lack of standardization created significant challenges for developers seeking to build AI systems that could seamlessly interact with a wide range of external data sources. Solutions like LangFlow have attempted to address this issue by standardizing some of the tooling and enabling interaction with multiple LLMs within a specific framework.
MCP takes the concept of standardization to a new level, allowing for the creation of integrations that can be reused across multiple solutions. This effectively breaks down the silos that previously existed, facilitating a more cohesive and interoperable AI ecosystem. By providing a common standard for communication between LLMs and external data sources, MCP is enabling developers to build more sophisticated and versatile AI systems.
How to Begin Working with MCP
To begin your journey with MCP, you will require a host application (referred to as a ‘client’) and a server. The host application serves as the central orchestrator, managing the communication flow between the LLM and the interfaces that connect to the MCP servers.
A fundamental example of this is using Claude Desktop to integrate a filesystem MCP server, as detailed in the Quickstart for Claude Desktop Users guide. This guide demonstrates the process of adding a filesystem server to Claude Desktop, enabling it to provide local filesystem information to Claude.ai. While Claude Desktop serves as a valuable proving ground for MCP servers, numerous other clients offer enhanced user experiences and features.
Online directories of MCP clients and servers are steadily emerging, such as MCP Clients | Glama and Open-Source MCP Servers | Glama, providing developers with invaluable resources and a growing ecosystem of tools and services.
How Does MCP Function?
MCP operates on a client/server architecture, enabling LLMs to interact with external data in a seamless and structured manner. This architecture is composed of three primary components:
Host: The host application serves as the central hub, managing interactions between LLMs and multiple MCP clients. Popular MCP hosts include Claude Desktop, Claude Code, Cursor, Windsurf, and editor integrations like Cline and Continue. The host is responsible for orchestrating the flow of data and requests between the LLM and the various MCP servers.
Client: The client functions as an interface within the host application, facilitating communication between the LLM and the server. It maintains a one-to-one connection with the server, translating requests from the LLM into a format that the server can understand and vice versa.
Server: The server is a compact application that communicates with the client using the MCP protocol. It provides standardized processes for listing its capabilities and responding to requests for relevant data or actions. The server is responsible for accessing and managing the external data source.
While these components are typically discussed as separate entities, they can be integrated into a single application or exist as independent applications. Currently, the most common configuration involves the client being integrated into the host application, communicating with the server over secure transports using JSON-RPC. This configuration offers a balance between flexibility and security.
What Capabilities Do MCP Servers Offer?
MCP servers provide clients with a rich set of capabilities designed to support data retrieval and the execution of actions on that data. These capabilities include:
Resources: Data stores that the LLM can track, such as files, database schema information, and console logs. Resources are loaded at the beginning of a chat session to avoid repeated requests for static data. This reduces latency and improves efficiency.
Tools: Actions that can be performed, such as retrieving content from files, inserting data into a database, or replying to emails. Tools provide the LLM with the ability to interact with the external world and perform tasks beyond its inherent capabilities.
Prompts: Useful and reusable prompts provided by the server to the client. Many host applications allow users to list available prompts using a “quick list” feature, often triggered by typing a “/“. These prompts can also serveas templates that can be dynamically populated with user inputs. Prompts can guide the LLM in its interactions with the server and ensure that requests are formulated in a way that the server can understand.
Currently, ‘tools’ are considered the most impactful capability offered by MCP, and they tend to garner the most attention from developers and users alike. The ability to extend the LLM’s capabilities through the use of external tools is a key driver of MCP’s adoption.
Is MCP Server Usage Safe?
MCP inherently relies on trust, encompassing several key areas:
- Trust that the host application effectively controls access to the clients, preventing unauthorized access and ensuring that only authorized clients can interact with the server.
- Trust that the client uses secure transports when communicating with the server, protecting data in transit from eavesdropping or tampering.
- Trust that the server implements secure practices when accessing resources, preventing data breaches and ensuring the confidentiality and integrity of sensitive information.
Users should prioritize MCP servers from reputable sources and always exercise caution by verifying the integrity of the software before installation. This helps to mitigate the risk of installing malicious servers that could compromise the security of their systems.
How Does the MCP Host Implement Security?
The host application should implement robust controls that allow the user to explicitly approve tools before they are used. This ‘just-in-time’ approval mechanism helps to prevent unauthorized actions and ensures that the user is aware of the potential impact of each tool. Mainstream applications often incorporate mechanisms to verify the acceptability of tool usage. For example, Claude Desktop prompts the user to choose between ‘use once’ or ‘use for the entire chat session’ when a tool is called for the first time. This provides the user with granular control over the use of external tools. Other applications, like Cline, may have methods to automatically approve certain tools or applications based on pre-defined criteria. The level of information presented to the user in these verification dialogs can vary depending on the host application.
What Transport Security Controls Are Available?
Two primary transport mechanisms are currently in use: STDIO and Server Sent Events (SSE).
STDIO is the preferred choice when the client and server reside on the same computer. It directs the client’s output to the server’s input and vice versa. The transport can only be compromised if the local system itself is breached, providing a relatively high level of security.
SSE is employed when the client and server are located on different computers. It transports JSON messages over HTTP connections, enabling the use of standard HTTP security options like SSL transports and Open Authentication (OAuth) authorization. This provides a means of securing communication over a network.
What Are the Biggest Risks of Using MCP?
The most significant risk associated with MCP is the potential injection of malicious servers into the system. Because all registered servers have a single point of reference within the host application and LLM, malicious servers could potentially poison the LLM by feeding it false or misleading information, or exploit the tools of legitimate servers for malicious purposes. As the MCP ecosystem continues to evolve, the formalization of concepts such as MCP security certification, server integrity monitoring, and the standardization of logging for monitoring are expected. These measures will help to improve the overall security of the MCP ecosystem. MCP ‘App Stores’ are also likely to emerge, providing centralized repositories for easily integrating MCP servers into existing tools. This will provide a more controlled and secure environment for discovering and installing MCP servers.
While the MCP specification strongly recommends authentication and authorization for remote servers, it does not mandate them. This means that developers of MCP servers may overlook the importance of network security and fail to implement these critical security measures.
Remotely accessible MCP servers are inherently vulnerable to man-in-the-middle attacks and remote exploits. Therefore, any MCP servers that utilize network-based transport mechanisms must implement robust authentication and authorization mechanisms to protect themselves from these threats.
How Can I Protect My Information When Using MCP?
As technical solutions and capabilities for securing MCP solutions continue to evolve, the current recommendation is to adhere to established cybersecurity best practices. Key steps include:
Detect and inventory your MCP installations and configurations across your environment. Given MCP’s early stage of adoption, this requires a more hands-on approach involving close inspection of endpoints for configuration files, rather than relying on centralized monitoring. Understanding and approving MCP usage is critical for maintaining environmental integrity. This helps to prevent unauthorized MCP installations and configurations.
Control access and monitor the resources that MCP servers are accessing. Whether the resources are local to the endpoints or SaaS applications, monitoring access through logging and auditing is essential. This provides visibility into the activities of MCP servers and helps to detect any suspicious behavior.
Train the people that are using MCP in their job duties. Ensure they understand the impact of a tool before authorizing its use. The MCP specification emphasizes the user’s consent and authorization before operations are performed. Training provides the understanding required to make informed decisions about which tools to authorize and when. This empowers users to make informed decisions and helps to prevent accidental or malicious misuse of MCP.