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Model Context Protocol (MCP)

Standardized integration protocol for connecting AI models to external tools and data sources

What is Model Context Protocol?
Understanding the open standard for AI model integration

The Model Context Protocol (MCP) is an open-source standard introduced by Anthropic in November 2024 that provides a universal interface for connecting large language models (LLMs) and AI applications to external tools, systems, and data sources. MCP enables AI models to access real-time data and execute functions beyond their initial training, making them more useful and context-aware in production environments.

Key Characteristics

  • Open Standard: Freely available protocol that anyone can implement
  • Client-Server Architecture: AI applications (clients) communicate with MCP servers that expose capabilities
  • Multi-Language Support: SDKs available in Python, TypeScript, Java, Go, Rust, and more
  • Secure by Design: Built with security and permission management in mind
  • Extensible: Supports custom tools, resources, and prompts for domain-specific needs

Core Components

Tools

Functions that AI models can call to perform actions, such as querying databases, executing code, or interacting with APIs.

Resources

Data sources that AI models can read from, such as files, databases, or external APIs.

Prompts

Reusable prompt templates that can be dynamically populated with context from resources.

Why MCP Matters for AI Development
  • Standardized Integration: Eliminates the need for custom integrations between every AI application and external service, reducing development time and complexity.
  • Real-Time Data Access: Enables AI models to work with current, live data rather than being limited to their training data, making them more useful in production.
  • Tool Integration: Allows AI models to perform actions, not just generate text, enabling more sophisticated workflows and automation.
  • Vendor Independence: Open standard means you're not locked into a single vendor's ecosystem, providing flexibility and future-proofing.
  • Security and Permissions: Built-in mechanisms for controlling what AI models can access and do, critical for enterprise deployments.
Industry Adoption

MCP has rapidly gained adoption from major AI providers and tech companies:

  • OpenAI: Integrated MCP into ChatGPT desktop app, Agents SDK, and Responses API (March 2025)
  • Google DeepMind: Announced support for MCP in upcoming Gemini models and infrastructure (April 2025)
  • Microsoft: Integrated MCP into GitHub, Microsoft 365, and Azure platforms
  • Anthropic: Original creator and maintainer of the protocol