Should you build an MCP server or a custom API integration for your AI tool? Here’s when each makes sense.
MCP wins when
- You want your integration to work with multiple AI hosts (Claude, Cursor, VS Code, GPT)
- You’re building a reusable tool that others might use
- You want standardized security and auth patterns
- You need the AI to discover tools dynamically
Custom integration wins when
- You only use one AI provider
- You need maximum performance (MCP adds protocol overhead)
- Your integration is deeply embedded in your application
- You need features MCP doesn’t support yet
Effort comparison
| MCP Server | Custom Integration | |
|---|---|---|
| Initial build | 2-4 hours | 1-2 hours |
| Works with | Any MCP host | One provider |
| Maintenance | Low (standard protocol) | Higher (API changes) |
| Reusability | High | Low |
| Community | Can publish for others | Internal only |
My recommendation
Start with MCP. The upfront cost is slightly higher, but you get compatibility with every major AI tool. If you later need custom performance, add a direct integration alongside MCP.
See our build tutorials to get started.
Related: MCP Complete Guide · Build MCP Server (TypeScript) · Best MCP Servers