MCP vs Custom APIs
When to use MCP versus building custom API integrations. Decision framework for developers.
This article is part of our Comparison series.
Read the complete guide: What is MCP?You could build custom API integrations for your AI application. Or you could use MCP. Both work—but they're suited for different situations. This comparison helps developers decide: when does MCP make sense, when should you build custom, and when might you use both?
Quick Comparison
| Factor | MCP | Custom APIs |
|---|---|---|
| Development Time | Minutes to Hours | Days to Weeks |
| Flexibility | Standardized Patterns | Unlimited |
| Maintenance | Community / Vendor | You (100%) |
| Learning Curve | MCP Protocol | Your Stack |
| Best For | Standard Tools & Speed | Highly Custom Systems |
What MCP Gives You
- Pre-built Integrations
Gmail, Drive, Slack, GitHub—ready to use in minutes. No API wrapper coding required.
- Standardized Protocol
Consistent behavior. Claude already knows how to "speak" MCP.
- Local-First Architecture
Runs locally. No need to stand up cloud infrastructure just to connect a tool.
What Custom APIs Give You
- Complete Control
Exact data formatting, custom error handling, and precise logic control.
- No Constraints
Not limited by MCP features. Use any auth method, any protocol features.
- Performance Optimization
Tailor caching, batching, and query performance specifically for your app.
Decision Framework
- Integrating with common SaaS tools (Google, Slack)
- Time-to-value is critical
- Building specifically for Claude
- You want community implementation maintenance
- Rapid prototyping / MVP phase
- Integrating with proprietary internal systems
- Complex business logic is required in the layer
- Building for multiple LLM providers (non-MCP)
- Specific high-performance requirements
- You need total control over the stack
Development Effort: Real World
Let's look at the time investment for two common scenarios.
- Install server: 5 min
- Configure: 10 min
- Test: 15 min
- Google Cloud Setup: 30 min
- Auth Implementation: 2-4 hours
- API Wrapper: 2-4 hours
- Tool Definitions: 1-2 hours
- Build MCP Server: 4-8 hours
- Test with Claude: 1-2 hours
- Build API Endpoint: 2-4 hours
- Tool Definitions: 1-2 hours
- Testing: 1-2 hours
Observation: For standard tools, MCP is 10-20x faster. For internal custom tools, the effort is comparable, but MCP provides the benefit of a standardized protocol that preserves context better.
Technical Comparison
Authentication
MCP: OAuth tokens managed locally by the server or keychain. Standardized credential handling.
Custom: You build the auth flow, manage refresh tokens, and handle secure storage yourself.
Maintenance
MCP: Community or vendor maintains the code. You just update the package.
Custom: You own every bug, every API depreciation, and every feature request.
LLM Integration
MCP: Claude automatically discovers capabilities. "Plug and Play".
Custom: You manually define schemas, feed them to the model, and parse the output.
The Hybrid Approach
It's not usually an "either/or" decision. The best architectures often use both.
Claude Desktop
│
├── MCP Servers (Standard Tools)
│ ├── Gmail MCP
│ ├── Google Drive MCP
│ └── Slack MCP
│
└── Custom Integration (Internal)
├── Internal Database
├── Proprietary API
└── Custom Business Logic
Strategy: Use MCP for the commodity layers (email, chat, files) where you don't need to reinvent the wheel. Reserve your custom monitoring/API development time for the 20% of your stack that is truly unique to your business.
You can even wrap your Custom API inside an MCP server. This gives you the control of custom code with the standardized "plug-ability" of MCP.