DZone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
Please enter at least three characters to search
Refcards Trend Reports
Events Video Library
Refcards
Trend Reports

Events

View Events Video Library

Zones

Culture and Methodologies Agile Career Development Methodologies Team Management
Data Engineering AI/ML Big Data Data Databases IoT
Software Design and Architecture Cloud Architecture Containers Integration Microservices Performance Security
Coding Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks
Culture and Methodologies
Agile Career Development Methodologies Team Management
Data Engineering
AI/ML Big Data Data Databases IoT
Software Design and Architecture
Cloud Architecture Containers Integration Microservices Performance Security
Coding
Frameworks Java JavaScript Languages Tools
Testing, Deployment, and Maintenance
Deployment DevOps and CI/CD Maintenance Monitoring and Observability Testing, Tools, and Frameworks

Modernize your data layer. Learn how to design cloud-native database architectures to meet the evolving demands of AI and GenAI workkloads.

Secure your stack and shape the future! Help dev teams across the globe navigate their software supply chain security challenges.

Releasing software shouldn't be stressful or risky. Learn how to leverage progressive delivery techniques to ensure safer deployments.

Avoid machine learning mistakes and boost model performance! Discover key ML patterns, anti-patterns, data strategies, and more.

Related

  • How Generative AI Is Revolutionizing Cloud Operations
  • A Comprehensive Guide to Generative AI Training
  • Using Snowflake Cortex for GenAI
  • Redefining Ethical Web Scraping in the Wake of the Generative AI Boom

Trending

  • Measuring the Impact of AI on Software Engineering Productivity
  • The Cypress Edge: Next-Level Testing Strategies for React Developers
  • AI-Assisted Coding for iOS Development: How Tools like CursorAI Are Redefining the Developer Workflow
  • Securing Parquet Files: Vulnerabilities, Mitigations, and Validation
  1. DZone
  2. Data Engineering
  3. AI/ML
  4. Is the Model Context Protocol a Replacement for HTTP?

Is the Model Context Protocol a Replacement for HTTP?

MCP works with HTTP, not replaces it. It’s a higher-level framework for managing how AI models handle context, applications, and memory during interactions.

By 
Vijay Joshi user avatar
Vijay Joshi
·
Apr. 18, 25 · Analysis
Likes (5)
Comment
Save
Tweet
Share
4.7K Views

Join the DZone community and get the full member experience.

Join For Free

With the rise of AI-native applications and agentic systems, a community of developers is being introduced to new techniques, abstractions, and architectural patterns that didn’t exist a few years ago. One term gaining traction — especially in the LLM and Generative AI ecosystem — is the Model Context Protocol.

With its rise and attention, it's also generating confusion and raising the following question:

Is MCP a new transport protocol that replaces HTTP?

The short answer to this one is: No.

In this article, we will try to understand the following questions, which will help us to understand the key differences between these two protocols:

  • What MCP actually is
  • How it differs from HTTP
  • Why this confusion is understandable
  • How they can work together in AI applications

What Is the Model Context Protocol?

The Model Context Protocol is a protocol to define how AI models interact with context including memory, tools, functions, user preferences, and system instructions across sessions.

Think of MCP as an application-layer protocol specifically designed to help AI models work more intelligently and efficiently within structured architecture patterns and environments.

It manages things like:

  • How context is initialized and updated
  • How the model decides which tools or functions to call
  • How memory is written to or retrieved during a session
  • What assumptions the model can make about the user or task

MCP is essential for enabling agent-like behavior, where an AI system can make decisions across multi-step tasks with access to stateful information and external tools. It is important to note that MCP is not a transport protocol. It does not manage itself with how bytes move across a network.

What Is HTTP, Then?

HTTP is the foundational protocol of the web. It is a well-established transport protocol that defines how requests and responses are formatted and transmitted between clients and servers.

  • It enables web browsing.
  • It is the foundational protocol of REST APIs.
  • It's how most modern applications communicate over the internet.

Here are the key distinctions:

Aspect MCP HTTP
Purpose Defines how AI context is structured Transports data across the network
Scope Application-specific to model sessions General-purpose communication layer
Focus Context, memory, tools, agent behavior Request/response messaging
Transport Layer? No Yes


Why the Confusion?

It's easy to see why we could mix the two up:

  • They are both called protocols and follow client-server topologies. It is important to understand that “protocol” is a broad term. MCP operates at a much higher abstraction level.
  • MCP is new and fitting in the context of contextual AI-related communications, so documentation and mental models are still forming, and we will see more in this space.
  • MCP’s introduction feels infrastructural, like HTTP or WebSocket. But it’s really more of a conversation manager for models, not a network stack.

How MCP and HTTP Work Together

Rather than replacing HTTP, MCP is meant to run on top of HTTP, WebSockets, or any other transport layer.

Think of other examples, such as GraphQL working over HTTP,  gRPC running over HTTP/2, and JSON being encoded and sent over HTTP.

In the same way, MCP defines the semantics of how a model processes requests, while HTTP moves those requests between client and server.

An AI application might send an MCP-compliant request payload over HTTP. That payload includes everything the model needs to operate intelligently: previous messages, tool availability, user memory, function definitions, and so on.

What Could We Infer?

  • Given its definition, MCP is not a transport protocol, and it doesn’t replace HTTP.
  • MCP is a higher-level protocol for managing contextual AI interactions.
  • It’s tightly coupled to how AI agents will work moving forward that includes memory, tools, and reasoning.
  • In other words, MCP and HTTP are complementary, not competitive.

Conclusion

As we shift toward AI-native software architecture, understanding new concepts like MCP will be critical. It’s part of a broader movement to build more intelligent, persistent, and capable AI systems that can function as true agents.

But let’s be clear: HTTP is still doing the heavy lifting under the hood.

MCP changes how we talk to AI models, not how the data gets from point A to point B.

AI Protocol (object-oriented programming) generative AI large language model

Published at DZone with permission of Vijay Joshi. See the original article here.

Opinions expressed by DZone contributors are their own.

Related

  • How Generative AI Is Revolutionizing Cloud Operations
  • A Comprehensive Guide to Generative AI Training
  • Using Snowflake Cortex for GenAI
  • Redefining Ethical Web Scraping in the Wake of the Generative AI Boom

Partner Resources

×

Comments
Oops! Something Went Wrong

The likes didn't load as expected. Please refresh the page and try again.

ABOUT US

  • About DZone
  • Support and feedback
  • Community research
  • Sitemap

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • Become a Contributor
  • Core Program
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 3343 Perimeter Hill Drive
  • Suite 100
  • Nashville, TN 37211
  • support@dzone.com

Let's be friends:

Likes
There are no likes...yet! 👀
Be the first to like this post!
It looks like you're not logged in.
Sign in to see who liked this post!