Model Context Protocol
Also known as: MCP
An open standard developed by Anthropic that standardizes how AI applications connect to external data sources, tools, and context providers through a unified protocol.
“An open standard developed by Anthropic that standardizes how AI applications connect to external data sources, tools, and context providers through a unified protocol.
“
Overview
The Model Context Protocol (MCP) is an open standard designed to solve the "N×M integration problem" in AI context management. Without a standard protocol, every AI application would need custom integrations for every data source. MCP provides a universal interface — similar to what USB did for hardware peripherals — allowing any AI application to connect to any MCP-compatible data source.
Architecture
MCP follows a client-server architecture:
- MCP Hosts: AI applications (like Claude Desktop, IDEs, or custom apps) that need context
- MCP Clients: Protocol clients within the host application that maintain connections to servers
- MCP Servers: Lightweight programs that expose specific data sources or capabilities through the standardized protocol
Core Capabilities
Resources
MCP servers can expose data and content that the AI application can read and use as context. Resources can be files, database records, API responses, or any structured data.
Tools
Servers can expose executable tools that the AI model can invoke — searching databases, creating records, calling APIs, or performing computations.
Prompts
Servers can provide pre-built prompt templates that help structure interactions with the AI model for specific use cases.
Why MCP Matters for Context Management
MCP directly addresses the core challenge of enterprise context management: connecting AI systems to the right data at the right time. By standardizing these connections, MCP enables organizations to build modular, maintainable, and interoperable AI infrastructure that can scale across diverse data sources and tools without custom integration work for each pair.
Adoption
Since its release, MCP has been adopted by major development tools and AI platforms. Companies like Block, Apollo, Replit, and Sourcegraph have built MCP servers, and IDE platforms like Cursor and Windsurf have integrated MCP client support.
Sources & Further Reading
Related Terms
Context Window
The maximum amount of text (measured in tokens) that a language model can process in a single interaction, determining how much information the model can consider when generating a response.
Function Calling
A capability of AI models to generate structured outputs that invoke predefined functions or APIs, enabling AI systems to take actions, retrieve data, and interact with external systems.
Large Language Model
A type of AI model trained on vast amounts of text data that can understand, generate, and manipulate human language, typically based on the transformer architecture with billions of parameters.
Retrieval-Augmented Generation
A technique that enhances AI model outputs by retrieving relevant information from external knowledge sources and incorporating it into the model's context before generating a response.