MCP (Model Context Protocol)
Model Context Protocol is an open standard that allows AI assistants to securely connect with external data sources and tools. MCP enables AI to access databases, APIs, file systems, and other services in a standardized way, extending what AI can do beyond just generating text.
Origin
Introduced by Anthropic in late 2024 as an open protocol to standardize how AI applications connect to external systems, preventing fragmentation across different AI tools.
Example
MCP solves a fundamental limitation of AI: models only know what's in their training data or what you paste into prompts. With MCP, AI can reach out to get current, relevant information.
The Problem MCP Solves
Without MCP:
- Manually copy-paste context into prompts
- AI doesn't know your database schema
- Can't access private documentation
- Each tool builds custom integrations
With MCP:
- AI pulls context automatically
- Understands your actual systems
- Accesses private knowledge bases
- Standardized across tools
How MCP Works
Your Request → AI Assistant → MCP Server → Data Source
↓ ↓
AI Response ← Context Retrieved ←
- AI recognizes it needs external data
- Calls appropriate MCP server
- Server retrieves and returns data
- AI uses data to generate better response
Common MCP Integrations
- Databases — AI understands your actual schema
- Documentation — Pull from Notion, Confluence, etc.
- Code repositories — Access across repos
- APIs — Query external services
Why MCP Matters for Vibe Coding
The more context AI has, the better it performs. MCP dramatically expands available context beyond what fits in a prompt, making AI assistants genuinely useful for real-world development.
Cursor
Emergent — An agentic vibe-coding platform that builds production-ready apps