The Universal Standard for Agentic AI Integration
Before MCP, connecting AI applications to external tools was a nightmare. Each connection was a custom, brittle, and expensive project, leading to a combinatorial explosion of work known as the "N×M integration problem."
AI Applications
External Services
Result: N × M Custom Connectors
Expensive, time-consuming, and impossible to maintain.
Introduced by Anthropic on November 25, 2024, MCP provides a universal, model-agnostic interface. It creates a "plug-and-play" environment, solving the N×M problem by standardizing how AIs and tools communicate.
A common language for all AI-tool interactions, eliminating vendor lock-in.
Combine small, focused servers (e.g., Slack, GitHub) to create powerful, multi-tool workflows.
Built on a foundation of explicit user consent and control for all actions.
MCP uses a three-participant model to ensure a clear separation of concerns and a strong security boundary. This design was heavily influenced by the proven success of the Language Server Protocol (LSP).
e.g., Claude Desktop, Zed IDE
The main AI application. Orchestrates logic, manages security, and gets user consent.
Lives inside the Host
Handles low-level protocol communication for a single, dedicated connection to a server.
e.g., GitHub Server, Slack Server
A lightweight wrapper that exposes a tool's capabilities via the MCP standard.
Primitives are the fundamental building blocks of the protocol, defining the types of capabilities that can be exchanged. This bidirectional communication enables complex, collaborative workflows.
MCP is standardizing on OAuth 2.1 (Authorization Code with PKCE) for secure, delegated access to remote services. This ensures users grant specific permissions without ever sharing their passwords.
1. User Action
2. Agent Redirects
3. User Consents
4. Get Auth Code
5. Exchange for Token
6. Access Resource
MCP's success is driven by its rapid, widespread adoption. From developer tools to enterprise platforms, a rich ecosystem of servers and hosts is growing daily.
Major players across diverse industries are building on MCP.
The protocol is supported by official SDKs and a growing library of reference servers.
MCP and Retrieval-Augmented Generation (RAG) are not competitors; they are complementary technologies. The most powerful AI systems use both.
Is about KNOWING
Retrieves information from a static knowledge base (like PDFs or documents) to provide factual context for an LLM's response.
Is about DOING
Interacts with live, dynamic systems via tools to query real-time data or perform actions with side effects (like sending an email).