Model Context Protocol Decoded: What it is and How to Use it

Model Context Protocol Decoded: What it is and How to Use it

The cybersecurity battle is constant. Attackers innovate relentlessly while defenders grapple with overwhelming alerts and siloed tools. Artificial Intelligence (AI) promises powerful features, but a lack of real-time context and integration challenges have hampered its effectiveness in security automation. Now, Model Context Protocol (MCP) is emerging as a game-changing open standard, heralding a new era of intelligent security operations (SecOps).

The AI Automation Bottleneck in Cybersecurity

Despite AI’s promise, security operations centers (SOCs) face persistent hurdles:

• Alert Overload: A flood of alerts obscures genuine threats.
• Tool Silos: Disconnected tools prevent a unified security view.
• Missing Context: AI needs rich, real-time data from diverse sources to make smart decisions, a historically difficult task.
• Rigid Integrations: Connecting AI to security tools often requires custom, inflexible solutions.

These issues limit AI’s ability to be the decisive force multiplier security teams desperately need.

What is Model Context Protocol (MCP)? 

MCP, an open standard created by Anthropic, acts like a universal adapter, enabling AI models to seamlessly communicate with external tools, data sources, and services. It standardizes how AI gets the context it needs.

MCP uses a client-server architecture:

• MCP Host: An AI application (e.g., an AI assistant like Hero AI) that needs external data or actions. It runs MCP Clients.
• MCP Client: Within the Host, it discovers and communicates with an MCP Server.
• MCP Server: A wrapper around a specific tool (like Swimlane Turbine), database, or API, exposing its functions and data in a standardized way.

Top 5 MCP Benefits:

1. Interoperability: A common language reduces complex custom integrations. If a tool has an MCP server, any MCP-compliant AI host can interact with it.
2. Real-Time Context: AI models query MCP servers for live, up-to-date information.
3. Extensibility: AI agents can easily connect to a growing ecosystem of MCP-enabled tools and data.
4. Enhanced Security: MCP facilitates secure, auditable access to resources.
5. Development Efficiency: Build an MCP server once, and many AI agents can use it.

How MCP is Used in Cybersecurity Automation

For cybersecurity, MCP’s impact is transformative. It allows AI agents to securely access and act upon data from across the security toolchain:

• Unified Visibility: An AI security agent can connect to MCP Servers for SIEM, EDR, threat intelligence, and more, achieving a holistic view.
• Intelligent Triage: Richer context from multiple MCP-connected sources enables AI to perform more accurate alert triage, reducing false positives.
• Dynamic Response: AI agents can use MCP to trigger actions in connected security tools (e.g., isolate an endpoint via an EDR’s MCP server) as part of an automated response.

Imagine an AI assistant that, upon seeing a suspicious IP, automatically queries threat feeds, checks internal logs, and recommends actions—all orchestrated via MCP.

Swimlane and MCP: Boosting SecOps with Adaptive Automation 

To show the promise of MCP and the power and flexibility of Swimlane Turbine, we built an example playbook that uses MCP to give Hero AI the agency to communicate with VirusTotal, Slack and Firecrawl.

With a simple prompt, the action knows to check an indicator of compromise (IOC) with VirusTotal. If the IOC isn’t benign, it summarizes the verdict in a message to other team members in Slack with a link for them to communicate if they wish to take further action. Items like the domain, Slack channel, and approval webhook were dynamically generated as a part of an automation playbook, giving Hero AI relevant real-time context.

The prompt below was generated after variables were replaced with the above-mentioned Swimlane Turbine playbook properties.

With just a few minutes in Turbine, we’ve built a sophisticated playbook that integrates with multiple tools, makes decisions, and notifies other teams. A playbook like this is not only effective and efficient, but it can be automatically updated or improved when the attached MCP servers are updated – requiring no changes to the existing playbook. See how it works in this 5-minute demo video.

Let’s break down what happened.

1. The AI captured a list of available tools using MCP.
2. The VirusTotal tool get_domain_report was chosen, and the domain was successfully selected and sent to the VirusTotal MCP server for processing. 
3. The AI interpreted the (lengthy) response from VirusTotal and made a decision to invoke the Slack steps.
4. In order to send a message to the required Slack channel, the Slack MCP server requires the channel ID. So, the AI first chose to use the get_channels tool to discover the correct channel ID given the provided channel name. 
5. The AI then summarized the results from VirusTotal in a message and invoked the send_message tool via the Slack MCP server. 
6. The AI then crafted an additional message, per the initial instructions, to provide the approval link to the Slack channel.
7. Finally, the AI summarized what was done with a status update and fed it back to the playbook for further processing.

The resulting Slack message looked like this:

The Future: Composable, Context-Aware Security

Swimlane’s adoption of MCP aligns with the future trajectory of AI in cybersecurity—a future that is:

• Composable: Modular security capabilities allow AI agents to select tools and data as needed.
• Context-Aware: AI operates with a deep, real-time understanding of specific situations.
• Collaborative: AI augments human analysts, automating tasks and freeing humans for strategic work.

MCP is a crucial enabler of Swimlane’s vision of more adaptable, extensible, and intelligent AI-driven cybersecurity automation. As MCP adoption grows, the ability to seamlessly connect and orchestrate diverse AI capabilities will redefine security operations, and Swimlane is positioning itself at the forefront of this transformation.