Panther MCP Server

Panther’s MCP server bridges the gap between security analysts and their data by turning rich threat intelligence workflows into conversational, AI‑driven interactions. Instead of manually querying logs or writing detection rules in a separate IDE, analysts can simply ask the assistant to “write a new rule for failed SSH logins” or “add a comment to alert abc123.” The server exposes a curated set of tools that map directly onto common security operations tasks, enabling natural‑language commands to be translated into precise API calls against Panther’s platform.

At its core, the server solves the problem of siloed security tooling. Analysts often juggle multiple dashboards, query editors, and ticketing systems to investigate alerts. By integrating detection authoring, log querying, alert triage, and source management into a single MCP interface, the server eliminates context switching. Developers building AI assistants can inject domain‑specific knowledge into prompts, while analysts gain instant access to the full breadth of Panther’s data lake and alerting engine without leaving the conversational UI.

Key capabilities include:

• Alert management: Create, update, and comment on alerts; trigger AI‑powered triage that produces actionable insights; retrieve summaries or event samples for rapid situational awareness.
• Data lake querying: Execute ad‑hoc SQL against Panther’s centralized log repository, fetch table schemas, and list available databases or tables—allowing analysts to pull arbitrary telemetry on demand.
• Scheduled query oversight: Inspect and retrieve details of recurring queries that drive automated reporting or compliance checks.
• Source inventory: Discover and inspect log sources, ensuring data ingestion pipelines are healthy and properly configured.
• Detection authoring: Write and tune detection rules directly from the IDE, streamlining the development cycle for security analytics.

Real‑world scenarios that benefit from this server include rapid incident response, where an analyst can immediately pull related events and start a triage conversation; continuous compliance monitoring, by querying scheduled reports through the assistant; or threat hunting, where ad‑hoc data lake queries surface new attack patterns without leaving the chat. The MCP integration also allows developers to embed these capabilities into custom workflows—such as automatically attaching triage summaries to ticketing systems or generating detection rule drafts that feed into version control.

What sets Panther’s MCP server apart is its tight coupling to the platform’s native APIs and the breadth of its toolset. By providing a unified conversational layer over detection, alerting, and data lake operations, it transforms routine security tasks into fluent, AI‑enhanced interactions that accelerate both analysis and remediation.