Model Context Protocol (MCP): An Overview

@online{awasthi2025model,
  author = {Awasthi, Satya Raj},
  title  = {Model Context Protocol (MCP): An Overview},
  year   = {2025},
  month  = may,
  url    = {http://satyarajawasthi.com.np/writing/mcp-overview}
}

The Model Context Protocol (MCP) is an open standard developed by Anthropic in November 2024 to standardize how AI models, particularly Large Language Models (LLMs), interact with external tools and data sources. Often compared to a "USB-C for AI," MCP simplifies integrations by providing a universal interface for seamless, secure, and scalable communication.¹²

Key Components

• MCP Host: The user-facing AI application (e.g., Claude Desktop, Cursor IDE) that interacts with users and coordinates data access.³
• MCP Client: Manages 1:1 connections between the host and servers, ensuring secure communication.⁴
• MCP Server: Lightweight adapters exposing specific capabilities (tools, resources, prompts) from local or remote systems (e.g., GitHub, Slack, PostgreSQL).⁵
• Protocol: Uses JSON-RPC 2.0 over STDIO (local) or HTTP+SSE (remote) for structured message exchange.⁶⁷

Core Features

• Tools: Enable actions like executing code or sending messages.⁸
• Resources: Provide read-only data access, like querying databases.⁹
• Prompts: User-controlled templates for guiding LLM interactions.¹⁰
• Sampling: Allows servers to request LLM completions, enhancing two-way communication.⁵

Benefits

• Standardization: Reduces integration complexity from M x N to M + N, similar to the Language Server Protocol (LSP).⁵
• Flexibility: Supports switching between AI models and tools without reconfiguration.¹¹
• Security: Implements OAuth 2.1, PKCE, and granular permissions for secure access.¹²
• Scalability: Supports diverse transports (STDIO, HTTP+SSE) and a growing ecosystem of pre-built servers.¹³

Use Cases

• Software Development: IDEs like Zed and Cursor use MCP for real-time code context and automation.¹
• Business Automation: Integrates with tools like Slack, Notion, and GitHub for workflow enhancement.¹³
• Data Access: Enables AI to query databases or fetch web data dynamically.⁸

Current State

• Adoption: Supported by OpenAI, Google DeepMind, and tools like Replit and Sourcegraph.⁷
• Ecosystem: Over 1,000 community-built servers and official integrations (e.g., Google Drive, Stripe).⁵
• Challenges: Lacks standardized authentication, requiring custom solutions, and has a learning curve for setup.¹⁴¹⁵

MCP is rapidly becoming a cornerstone for context-aware AI agents, transforming them from isolated chatbots to interoperable systems deeply integrated with real-world tools. For more details, visit modelcontextprotocol.io.³

References

1. [1] Anthropic. Introducing the Model Context Protocol. 2024. anthropic.com
2. [2] Anthropic. Model Context Protocol (MCP), Claude documentation. docs.anthropic.com
3. [3] Model Context Protocol. Introduction. modelcontextprotocol.io
4. [4] Microsoft Tech Community. Model Context Protocol (MCP): Integrating Azure OpenAI for Enhanced Tool Integration. techcommunity.microsoft.com
5. [5] DigitalOcean. Model Context Protocol tutorial. digitalocean.com
6. [6] Model Context Protocol. Core architecture. modelcontextprotocol.io
7. [7] Wikipedia. Model Context Protocol. en.wikipedia.org
8. [8] DiamantAI. Model Context Protocol (MCP) Explained. diamantai.substack.com
9. [9] Schmid, P. Model Context Protocol (MCP): An Overview. philschmid.de
10. [10] Koul, N. The Model Context Protocol (MCP): A Complete Tutorial. Medium. medium.com
11. [11] Sakal, N. MCP vs API: Model Context Protocol Explained. norahsakal.com
12. [12] Auth0. An Introduction to MCP and Authorization. auth0.com
13. [13] DataCamp. Model Context Protocol (MCP): A Guide With Demo Project. datacamp.com
14. [14] Composio. What Is Model Context Protocol (MCP)? Explained. composio.dev
15. [15] Hugging Face. What Is MCP, and Why Is Everyone Talking About It? huggingface.co