What is the MCP Protocol?

The Model Context Protocol (MCP) has emerged as one of the most significant developments in AI technology in 2025. Launched by Anthropic in November 2024, MCP is an open standard designed to bridge AI models with the places where your data and tools live, making it much easier to provide context to AI systems. It's often described as the "USB-C for AI applications" - a universal connector that allows different AI models to interact with various tools and data sources through a standardized interface.

The Problem MCP Solves

Before MCP, integrating AI models with external systems was a fragmented, labor-intensive process. For example, if you wanted your AI agent to access Google Drive and a SQL database, you'd need to integrate Google's API and a database driver separately, each with its own authentication, data format, and quirks. This created what Anthropic engineers call the "M×N problem" - the exponential challenge of connecting M different AI models with N different tools or data sources, with each pairing requiring custom code.

MCP elegantly solves this by providing a single protocol that can unlock many doors, allowing new tools to be added without changing the client.

How MCP Works

The protocol fundamentally revolves around three core primitives:

1. Tools: Executable functions that AI models can call
2. Resources: Structured data that models can access
3. Prompts: Instruction templates that guide AI behavior

MCP follows a client-server architecture:

• MCP Clients: AI models or applications that connect to MCP servers
• MCP Servers: Backend services that implement the MCP specification and expose data sources or tools to clients

The Meteoric Rise of MCP

What's remarkable about MCP is how quickly it has gained traction in the AI development community. In just four months, MCP went from being a neat protocol that Claude Desktop used and open-sourced, to being supported by all major IDEs, with AI tools adding MCP support, including OpenAI.

Since its launch last November, the Model Context Protocol from Anthropic has gone viral, generating buzz as a simple, standardized way to connect language models with tools and data. Its popularity was further cemented during the AI Engineer Summit in February 2025, when the community received announcements about the highly anticipated official registry and comprehensive deep dives into the protocol specification.

Recent Developments

The MCP ecosystem continues to evolve rapidly. In a notable development, OpenAI has recently rolled out support for MCP, despite it being created by Anthropic, their best-funded startup rival. OpenAI CEO Sam Altman announced this move in March 2025.

The latest MCP release includes several feature additions, such as JSON-RPC batching that allows packaging multiple LLM data requests into one large request for increased efficiency. It also improves notification mechanisms and upgrades the authorization mechanism to OAuth 2.1.

Real-World Applications

MCP is enabling exciting new applications across various domains:

1. IDE Integration: Previously, developers had to use separate tools to query databases in production applications. But with MCP, they can "talk" to databases directly from the IDE, which feels like a game changer!

2. 3D Modeling: One of the most viral MCP demos has been Blender MCP, which lets AI assistants create and modify 3D scenes in Blender using plain language. Users can simply describe what they want, and the AI, through Blender MCP, creates that scene in Blender.

3. Cross-Platform Workflows: Futuristic use cases include connecting Figma with VS Code, 3D modeling via Cursor, and controlling a 3D printer from Windsurf - all made possible with MCP.

4. Web Interaction: Microsoft has released Playwright MCP, which combines the protocol with their Playwright software, allowing LLMs to interact directly with webpages.

The Growing Ecosystem

Among the most used MCP servers are those providing access to GitHub, Google Drive, Slack, as well as web search servers like Brave Search. The ecosystem is rapidly enriching with more than 250 servers available in early 2025.

Major companies adopting MCP include:

• Block (formerly Square)
• Apollo
• Zed
• Replit
• Codeium
• Sourcegraph
• Microsoft
• OpenAI
• Cloudflare
• Sentry

Challenges and Concerns

Despite its promising future, MCP faces several challenges:

1. Security Vulnerabilities: Security researchers at Equixly have identified concerning vulnerabilities in MCP implementations, noting that fundamental security issues from decades past are reemerging in this new context. Their research indicates that 45% of MCP server developers claimed security risks were "theoretical" or "acceptable."

2. Protocol Limitations: Current challenges include finding and setting up MCP servers, which is still a manual process requiring developers to locate endpoints or scripts, configure authentication, and ensure compatibility. Additionally, MCP lacks a built-in workflow concept to manage sequences of tool calls.

3. Fragmented Adoption: While MCP's goal is to eliminate fragmentation, at this early stage not all AI platforms or models support MCP out-of-the-box. Some open-source efforts are bridging this gap with wrappers that allow OpenAI functions to call MCP servers, but universal adoption remains a work in progress.

The Future of MCP

The next wave of progress will be defined by how the community addresses these foundational challenges. If done right, MCP could become the default interface for AI-to-tool interactions and unlock a new generation of autonomous, multi-modal, and deeply integrated AI experiences.

Based on Anthropic's talk at the AI engineer conference last month, it sounds like an MCP server registry and discovery protocol is coming. This could unlock the next phase of adoption for MCP servers.

Why MCP Matters for Developers and Businesses

For developers, MCP represents a significant reduction in the complexity of AI integration. Instead of building custom connectors for each service, developers can leverage a growing ecosystem of MCP servers.

For businesses, MCP could accelerate the adoption of AI-enabled applications across industries by lowering the barriers to integration. It encourages a more open, collaborative AI ecosystem where companies might contribute connectors and improvements back to the MCP community.

Getting Started with MCP

If you're interested in exploring MCP, here are some resources to get you started:

1. Model Context Protocol Official Site - Main documentation and resources
2. GitHub Anthropic/model-context-protocol - Official repository with source code and examples
3. Cursor MCP Documentation - Official documentation on implementing MCP in Cursor AI

Conclusion

The Model Context Protocol represents a paradigm shift in how AI models interact with the world. By standardizing these interactions, MCP is doing for AI what APIs did for web services - making integration composable, reusable, and scalable.

We could soon live in a world where AI assistants are not confined to answering questions but are true co-workers. They'll use tools on our behalf, coordinate complex tasks, and adapt to new tools as easily as a new hire might – or perhaps even more easily.

As we move further into 2025, MCP's growth trajectory suggests it will continue to play a pivotal role in shaping the future of AI application development and integration. Whether you're a developer, business leader, or AI enthusiast, understanding MCP and its implications will be crucial for navigating the evolving AI landscape.

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This blog post was created on May 5, 2025, and reflects the current state of the MCP protocol as of this date. Given the rapid pace of development in the AI field, some details may have changed since publication.