Security teams don’t need more dashboards, they need faster answers. With AI agents becoming key players in the SOC,
SOCRadar’s new MCP Server lets those agents interact directly with live threat intelligence, securely, contextually, and in real time.
SOCRadar's MCP (Model Context Protocol) Server
acts as a secure bridge between AI models and SOCRadar’s threat intelligence platform. Designed for AI-native environments, it allows language models to directly query real-time intel using plain language, turning threat hunting into a simple interaction rather than a multi-step process.
Built for AI, Without Compromising Security
Unlike traditional integrations that require custom APIs and tight coupling, MCP is purpose-built for agent-driven environments. And while that promises flexibility, security isn’t an afterthought.
“At SOCRadar, we’ve built the MCP Server with a zero-trust foundation and multiple layers of security,” said Ensar Seker, CISO at SOCRadar. “Each AI agent interaction is authenticated through granular, tokenized access controls, ensuring that only authorized agents can retrieve specific types of intelligence. Additionally, all requests are audited and monitored in real time with behavioral anomaly detection to prevent misuse or unauthorized data access. Data integrity is preserved through cryptographic hashing and schema validation at every exchange point, ensuring what the agent receives is verified, relevant, and unaltered.”
In short, security teams can give their AI agents access without losing control over how that access is used or what gets exposed.
Beyond APIs: Intelligence That Understands Context
The MCP Server isn’t just another endpoint. It’s designed to speak the language of AI.
“MCP Server goes beyond basic APIs,” said Seker. “It’s designed to be agent-native, offering contextualized, prompt-ready threat intelligence in formats that LLMs and autonomous agents can parse without additional engineering overhead. While traditional APIs deliver raw data, MCP contextualizes it, embedding threat relationships, priority tags, and even human-readable summaries.”
This makes it possible for security teams to run AI-driven playbooks with less manual stitching. The MCP Server can connect directly into platforms like Cortex XSOAR, Microsoft Copilot for Security, or custom SOC frameworks using persistent websocket streams—enabling real-time decision-making instead of just static data pulls.
Preparing for Autonomous AI in the SOC
As SOCs begin to explore semi-autonomous or fully autonomous agents, the need for guardrails grows. SOCRadar is already planning ahead.
“As AI agents move toward autonomous decision-making, we’re embedding confidence scoring, risk-boundaries, and human-in-the-loop checkpoints into MCP’s response structure,” said Seker. “Future iterations of MCP will support adaptive intelligence delivery, where the type and volume of shared data depend on the agent’s authorization level, past behavior, and current operational context.”
SOCRadar is also exploring digital twin environments to help SOC teams simulate and evaluate how AI agents act on MCP data before running anything live.
From Interface Overload to “Just Ask”
Ultimately, the MCP Server is about simplifying how teams interact with cybersecurity tools. Instead of memorizing UIs, writing queries, or juggling filters, analysts can just ask things like: “What assets are exposed to the latest Citrix vulnerability?” or “Create a report on threat actors targeting U.S. energy firms this week.”
The MCP Server handles the backend translation, execution, and formatting, so teams can focus on decisions, not digging through data.
