MCP Panther MCP Server

Panther's Model Context Protocol (MCP) server provides functionality to:

Local serverstdioPython

What is the MCP Panther MCP server?

Connect MCP Panther to Claude, Cursor or any other MCP client and it stops being a tab you switch to. Panther's Model Context Protocol (MCP) server provides functionality to:. The mcp panther mcp server is what makes that connection.

Installation

The server ships on PyPI as For, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.

Available tools

The toolset is worth reading before you wire it up, because it tells you what the integration is really for:

  • add_alert_comment — Add a comment to a Panther alert
  • start_ai_alert_triage — Start an AI-powered triage analysis for a Panther alert with intelligent insights and recommendations
  • get_ai_alert_triage_summary — Retrieve the latest AI triage summary previously generated for a specific alert
  • get_alert — Get detailed information about a specific alert
  • get_alert_events — Get a small sampling of events for a given alert
  • list_alerts — List alerts with comprehensive filtering options (date range, severity, status, etc.)
  • bulk_update_alerts — Bulk update multiple alerts with status, assignee, and/or comment changes
  • update_alert_assignee — Update the assignee of one or more alerts
  • update_alert_status — Update the status of one or more alerts
  • list_alert_comments — List all comments for a specific alert
  • query_data_lake — Execute SQL queries against Panther's data lake with synchronous results
  • get_table_schema — Get schema information for a specific table

Credentials and setup notes

Configuration is passed through the environment: PANTHER_INSTANCE_URL, PANTHER_API_TOKEN. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.

Worth knowing first

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 14 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch MCP Panther.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

Where it fits

Plenty of database access servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. MCP Panther's toolset — add_alert_comment, start_ai_alert_triage, get_ai_alert_triage_summary and 11 more — is a fair guide to whether it matches your workflow. It is maintained by panther-labs; worth a glance at recent repository activity before you build anything load-bearing on it.

We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.

Available tools

ToolWhat it does
add_alert_commentAdd a comment to a Panther alert
start_ai_alert_triageStart an AI-powered triage analysis for a Panther alert with intelligent insights and recommendations
get_ai_alert_triage_summaryRetrieve the latest AI triage summary previously generated for a specific alert
get_alertGet detailed information about a specific alert
get_alert_eventsGet a small sampling of events for a given alert
list_alertsList alerts with comprehensive filtering options (date range, severity, status, etc.)
bulk_update_alertsBulk update multiple alerts with status, assignee, and/or comment changes
update_alert_assigneeUpdate the assignee of one or more alerts
update_alert_statusUpdate the status of one or more alerts
list_alert_commentsList all comments for a specific alert
query_data_lakeExecute SQL queries against Panther's data lake with synchronous results
get_table_schemaGet schema information for a specific table
list_databasesList all available data lake databases in Panther
list_database_tablesList all available tables for a specific database in Panther's data lake

How to install the MCP Panther MCP server

{
  "mcpServers": {
    "mcp-panther": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "-e", "PANTHER_INSTANCE_URL",
        "-e", "PANTHER_API_TOKEN",
        "--rm",
        "ghcr.io/panther-labs/mcp-panther"
      ],
      "env": {
        "PANTHER_INSTANCE_URL": "https://YOUR-PANTHER-INSTANCE.domain",
        "PANTHER_API_TOKEN": "YOUR-API-KEY"
      }
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

VariableDescriptionRequired
PANTHER_INSTANCE_URLEndpoint or connection string the server talks to.Yes
PANTHER_API_TOKENCredential the server authenticates with.Yes

Example prompts to try

  • Use MCP Panther to add alert comment.
  • Use MCP Panther to start ai alert triage.
  • Use MCP Panther to get ai alert triage summary.

Frequently asked questions

It connects MCP Panther to MCP-compatible AI assistants such as Claude and Cursor, exposing 14 tools (add_alert_comment, start_ai_alert_triage, get_ai_alert_triage_summary, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with MCP Panther directly.