Cortex MCP Server

The MCP Server for Cortex transforms a traditional threat‑intelligence platform into a programmable, AI‑friendly service. By exposing Cortex’s rich set of analyzers as MCP tools, the server lets language models such as Claude query observables—IP addresses, URLs, domains, files—and receive structured analysis results without leaving the conversational flow. This bridges the gap between human‑oriented security platforms and AI assistants, enabling automated enrichment and decision support directly within chat interfaces.

For developers building security workflows, the server solves a key pain point: integrating diverse threat‑intelligence feeds into a single, consistent API. Cortex already aggregates many external services (AbuseIPDB, VirusTotal, Urlscan.io) through its modular analyzers. The MCP server simply forwards the AI’s tool calls to these analyzers, handles authentication via an API key, and translates raw responses into JSON objects that MCP clients can consume. This eliminates the need to write custom connectors for each feed and keeps all analysis logic centralized within Cortex.

Key capabilities include:

• Observable Analysis: Run any enabled analyzer by name, passing the observable and optional parameters. The server returns a detailed result set that can be parsed or displayed by the AI.
• Analyzer Discovery: The MCP client can request a list of available analyzers, enabling dynamic tool selection based on context.
• Structured Responses: Results are returned in a machine‑readable format, preserving metadata such as confidence scores, timestamps, and source URLs.
• Secure Access: API‑key authentication ensures only authorized clients can trigger analyses, protecting sensitive threat data.

Typical use cases span incident response automation, threat hunting, and security awareness training. An AI assistant can prompt a user for an IP address, invoke the tool, and then generate a concise report that includes reputation scores, historical activity, and suggested mitigation steps—all within the same conversation. In a SOC setting, analysts can query multiple observables in parallel, letting the AI orchestrate batch analyses and synthesize findings into actionable tickets.

The server’s integration is straightforward: add the MCP endpoint to your AI client configuration, provide the required environment variables (, ), and enable the desired analyzers in Cortex. Once running, any MCP‑compatible workflow can treat the server as a first‑class tool provider, unlocking powerful threat‑intelligence capabilities without modifying the underlying language model.