MCPs
ClaudeCursor
Foundations
What is MCP?
Model Context Protocol basics and when to use MCP servers
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Model Context Protocol
MCP (Model Context Protocol) is a standard for connecting AI agents to external tools and data sources. Think of it as a plugin system for AI.
Core concepts
- MCP Server: a process that exposes tools and resources to the agent
- Tools: functions the agent can call (search, navigate, analyze)
- Resources: read-only data the agent can access (docs, schemas)
Common MCP servers
| Server | Purpose |
|---|---|
| Context7 | Fetch up-to-date library documentation |
| Playwright | Browser automation and testing |
| File system | Enhanced file operations |
| Database | Query databases directly |
When to use MCPs vs Skills
| Use MCPs when... | Use Skills when... |
|---|---|
| You need live external data | You need reusable instructions |
| The tool requires a running process | The task is pure text/code generation |
| Integration with APIs or browsers | Following a specific workflow pattern |
Key takeaway
MCPs extend what an agent *can do* (new capabilities). Skills guide *how* the agent works (new behaviors). Start with skills; add MCPs when you need external integrations.
Source: modelcontextprotocol.io. The full MCP specification and server registry.