Choosing between REST, GraphQL, and MCP isn’t just about what’s “new” or “popular.” It’s about what matches your project’s needs. As a junior developer, knowing the right tool for the right situation can save you time and frustration. This guide explains when to use each option — practically, simply, and with real examples.

1. When to use REST

Use REST if:

• Your app deals with simple resources that map cleanly to URLs.
• You want strong caching, simple debugging, and mature community support.
• You don’t need highly dynamic queries from the client side.

Example: A simple blog backend

In a blog platform:

GET /posts       # Get all blog posts
GET /posts/1     # Get the blog post with ID 1
POST /posts      # Create a new blog post
PUT /posts/1     # Update post 1
DELETE /posts/1  # Delete post 1

You can easily model Posts, Users, Comments, etc., using basic HTTP verbs (GET, POST, PUT, DELETE).

Why REST fits here:

• The structure is predictable.
• HTTP methods map directly to operations.
• It’s easy to work with browser tools and libraries like fetch, axios, etc.

Best for CRUD apps, backends for mobile apps, microservices.

2. When to use GraphQL

Use GraphQL if:

• You often need to fetch related or nested data in a flexible way.
• You want clients (the browser or app) to ask only for the fields they need.
• You aim to minimize the number of network requests.

Example: A product catalog for an e-commerce app

Instead of doing several REST calls for product info and reviews, you can query like this:

query {
  product(id: "123") {
    name
    price
    images {
      url
      altText
    }
    reviews {
      author
      rating
      comment
    }
  }
}

One request — and you get everything you need.

Why GraphQL fits here:

• You avoid over-fetching (getting too much data) and under-fetching (missing data).
• You optimize for mobile devices with slower networks.
• It fits applications where front-end developers move fast and want control over data.

Best for SPAs (Single Page Apps), mobile apps, dashboards.

3. When to use MCP

Use MCP if:

• You are building AI-first products that need an LLM (like Claude, GPT) to interact with live systems.
• You want dynamic two-way communication: models discovering and using tools at runtime.
• You need your app to be AI-native, not just AI-assisted.

Example: AI agent writing to a database

Rather than coding each interaction manually, the LLM can discover and use available operations:

# Example of calling an MCP-discovered tool

# Connect to the MCP client
mcp_client = MCPClient()

# Discover available tools
available_tools = mcp_client.list_tools()

# Find the tool for database insert
db_insert_tool = available_tools["insert_user"]

# Execute it
response = db_insert_tool.execute({
    "username": "new_user",
    "email": "user@example.com"
})

print(response)

The model didn’t need to “know” about the database beforehand. The MCP server described the tool, and the LLM used it.

Why MCP fits here:

• You can add, remove, and upgrade tools without re-training or re-prompting the model.
• LLMs work with APIs, databases, and storage in a universal way.
• It reduces the custom glue code you usually need when building agent-based apps.

Best for AI applications, AI agents, tool-using LLMs.

Quick comparison table

Bonus: 5 Quick Questions to Pick Between REST, GraphQL, and MCP

Conclusion

Choosing between REST, GraphQL, and MCP isn’t about hype — it’s about understanding your app’s needs:

• Pick REST if you need simplicity and broad tool support.
• Pick GraphQL if you want flexible queries and control over payload size.
• Pick MCP if you’re building apps where AI is the main actor, not just a helper.

Each approach fits a different future: REST for traditional apps, GraphQL for dynamic front-ends, and MCP for AI-powered systems.

FAQs