Security Team Connected Snyk, PagerDuty, and Slack to AI

The problem: alert fatigue meets context switching

Two security engineers covering a 200-service platform. PagerDuty fires 40+ alerts per week. Each alert requires checking Snyk for vulnerability context, Slack for recent deployment chatter, and the service registry for ownership. Triage for a single alert: 25 minutes of tab-switching before deciding severity.

Half those alerts turn out to be low-priority. But you cannot skip triage without risking the one that matters.

What they connected

Three MCP servers via DataFaucet:

Snyk (vulnerability scanning) — browsed Snyk dashboard for 60 seconds. Captured endpoints for project vulnerabilities, severity scores, fix availability, and dependency paths. Deployed as hosted MCP server.

PagerDuty (alerting) — same process on PagerDuty. Captured incident details, service maps, escalation status, and recent incident history.

Slack (security channel) — pointed at their #security-alerts and #deploys channels. Captured message search and thread context.

The workflow now

Alert fires. Instead of opening three tabs, the engineer asks one prompt:

"PagerDuty incident INC-4521 just fired. What vulnerability is it about, is there a fix available in Snyk, and did anyone deploy the affected service in the last 2 hours?"

Agent calls all three MCP servers. Returns: the CVE details with CVSS score, whether Snyk has a fix version, and the last deploy timestamp from #deploys channel.

Triage decision in 3 minutes instead of 25. For the 60% of alerts that are low-priority, the answer is immediate: "CVSS 3.1, no exploit in the wild, fix available in next patch cycle, no recent deploys. Low priority."

What changed

Before connecting the tools, the team had a backlog of un-triaged alerts. Now they clear the queue daily. The AI handles the data gathering; the human makes the judgment call.

They also started running proactive queries: "Which services have critical Snyk findings with no PagerDuty policy?" Found 3 services with unmonitored critical vulnerabilities in the first week.

Results after 4 weeks

• Alert triage: 25 minutes down to 3 minutes per incident
• Daily alert backlog: from 8-12 un-triaged to zero
• Proactive vulnerability discovery: 3 critical gaps found in week one
• False positive identification: 60% of alerts resolved without escalation

Setup details

Total setup time: under 5 minutes for all three servers. No API tokens manually created (DataFaucet captured auth from browser sessions). No custom code. Connected to Claude Desktop using the JSON config DataFaucet provides.

The PagerDuty server required their existing browser session. Snyk used the org-level API token visible in dashboard settings. Slack used the existing web session.

With DataFaucet, security teams can connect their entire incident response stack in one afternoon. No vendor integrations to wait for, no custom webhook code.

Related: Best MCP Servers for DevOps, Support Team Cut Response Time 60%, MCP Servers vs Webhooks.