The Future is Agentic: MCP and the Next Generation of Applications

As the foundational layer for AI connectivity becomes standardized, the horizon of what is possible expands dramatically. MCP is not merely an incremental improvement; it is a catalyst for a new generation of software, introducing both unprecedented opportunities and critical new challenges that organizations must navigate.

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The Road Ahead: How MCP Will Redefine Application Development

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The long-term trajectory of MCP points toward a future where software is not just "AI-enabled" but "AI-native." This paradigm shift will fundamentally redefine the nature of application development and the role of the developer.

The protocol is the critical missing link for creating truly autonomous AI agents that can understand a user's intent and orchestrate complex, multi-step tasks across dozens of systems without direct human intervention.  This "agentic future" is rapidly becoming a reality, validated by massive platform shifts from industry leaders. At its October 2025 DevDay, OpenAI announced an "Apps SDK" that allows developers to build full applications that run inside ChatGPT, with MCP as the foundational backend logic. This transforms ChatGPT from a chatbot into an operating system for AI agents, with apps from Zillow, Canva, and Coursera already demonstrating this new paradigm.

Similarly, Google has embraced MCP as a core component of its multi-agent strategy, releasing an open-source "Agent Development Kit (ADK)" to build sophisticated agentic systems that use the protocol. Google is also pioneering a complementary "Agent-to-Agent (A2A)" protocol, which builds on MCP's tool connectivity to enable different AI agents to discover, communicate, and collaborate with each other.

This agentic future will be powered by a burgeoning economic ecosystem built around MCP. We are already seeing the early stages of this, with the development of MCP Registries—like the one recently launched by GitHub—to serve as centralized discovery services for trusted servers. Perhaps the most profound indicator of this shift is the integration of MCP at the operating system level. Microsoft, for instance, is building support for the protocol directly into Windows 11, framing it as a foundational layer for creating a "safer agentic future" on the platform.  When a protocol becomes part of the OS, it signals its transition from an application-level technology to a core piece of computing infrastructure.

This evolution will change the very nature of software development. The current model often involves a developer writing imperative code that dictates a workflow, perhaps calling an AI for a specific, isolated task like summarizing text. In an MCP-driven world, the AI agent becomes the central orchestrator.  The developer's role will shift from writing monolithic application logic to building and maintaining the portfolio of high-quality, secure, and efficient tools (MCP servers) that the AI agent can choose from. Software development will become less about building a single program and more about creating a library of composable, AI-callable enterprise capabilities. This gives rise to a new and vital specialization: the MCP Server Developer, an expert whose craft is to build the secure bridges between an organization's critical systems and the new world of agentic AI.

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A Double-Edged Sword: Navigating the Critical Security Landscape of MCP

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With the immense power that MCP grants to AI systems comes commensurate risk. The protocol's ability to connect AI to live systems and execute actions makes it a high-value target for malicious actors. A responsible adoption strategy requires a clear-eyed and sober understanding of the critical security vulnerabilities inherent in this new landscape. This is not a reason to avoid MCP, but a mandate to approach it with expert guidance and a security-first mindset.

The core danger is that MCP gives an AI powerful ways to cause damage, and a compromised integration can serve as a backdoor into an organization's most sensitive systems.  The stakes are dramatically elevated; a successful prompt injection attack, which in a simple chatbot might lead to embarrassing output, could escalate to full remote code execution in an MCP-enabled system. 

The theoretical risks are now proven realities. In July 2025, a critical command injection vulnerability (CVE-2025-53967) was discovered in the popular Figma MCP server, allowing for remote code execution. Even more severe, a vulnerability in a client-side proxy tool, mcp-remote, (CVE-2025-6514, CVSS score 9.6) demonstrated how a malicious server could achieve remote code execution on the client's machine, a devastating attack vector.

Research and real-world analysis have identified a range of specific, critical vulnerabilities that organizations must defend against  :

• Tool Poisoning and Prompt Injection via Tools: This is a particularly insidious attack. An adversary can inject malicious instructions into the description field of a tool on an untrusted MCP server. When the AI model reads this description to understand the tool's function, it processes the hidden instructions, potentially leading it to exfiltrate data or perform unauthorized actions. 
• Command Injection and Token Theft: A poorly coded MCP server can be vulnerable to classic exploits. An attacker might be able to inject system commands through a tool's parameters or exploit a vulnerability to read sensitive data from the server's memory, such as OAuth tokens or API keys, which can then be used to access other systems.
• Server Spoofing and the "Rug-Pull": Attackers can create malicious MCP servers that perfectly mimic the names and descriptions of legitimate, trusted ones, tricking users or applications into connecting to them. In a "rug-pull" scenario, a developer of a popular and trusted open-source server could push a malicious update, compromising every system that automatically pulls the latest version. 

To address these systemic risks, the industry is beginning to adopt MCP Gateways. Similar to API gateways, these act as a centralized middleware layer to enforce consistent security policies, authentication, and logging across all MCP servers, allowing security teams to govern the entire agent ecosystem from a single point. Leading industry analysts like Gartner now advise enterprises to prototype internal MCP services to assess benefits but to strictly restrict exposure to external servers, enforcing mandatory security requirements like HTTPS and robust OAuth for all connections.

The MCP specification itself acknowledges these dangers and outlines key security principles, but it is crucial to understand that the protocol itself cannot enforce them. Security is the responsibility of the implementers—the developers of the Host applications and the MCP Servers. The protocol recommends best practices like the Principle of Least Privilege (servers should only have the minimum permissions necessary) and, most importantly, User Consent and Control (users must explicitly approve all sensitive actions). The specification states that there "SHOULD always be a human in the loop" for critical operations, a recommendation that security experts argue must be treated as a strict requirement.

The security posture of an AI application is therefore no longer determined by its own code alone. It is now a function of the entire chain of trust across the Host, the Client, and every single MCP Server it connects to. The system is only as strong as its weakest link. A vulnerability in a single, seemingly innocuous community-built server could potentially be used to attack the Host or even pivot to attack other, more secure servers.  This reality means that enterprise adoption of MCP cannot be a free-for-all. It necessitates a new layer of governance, such as a formal "MCP Server Vetting Process" or an internal "Approved Server Registry," to ensure that only secure, audited, and trusted integrations are allowed to connect to the organization's AI ecosystem.

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Ready to Navigate the Agentic Future?

The shift to MCP-powered, agentic systems is no longer theoretical. Organizations that move early—and responsibly—will define the next generation of intelligent software.

If you’re exploring MCP adoption, agentic architectures, or secure AI integration, Switch’s Innovation Hub can help you evaluate opportunities, prototype safely, and design a governance-first roadmap tailored to your enterprise.

And in case you missed it, start the journey by revisiting Part II of this series: The Strategic Value of MCP Adoption