A 4-person IT helpdesk team at a 600-person company handled ~80 tickets per day. Each resolution required checking three systems: ServiceNow for ticket history, Okta for user provisioning status, and Jira for any related engineering work. Average resolution: 45 minutes.
The team wasn't slow. They were drowning in context-switching between dashboards.
Three MCP servers, each created in under a minute with DataFaucet:
1. ServiceNow (tickets, knowledge base, asset inventory)
Browse the ServiceNow instance for 30 seconds. DataFaucet captured endpoints for querying incidents, reading knowledge articles, and checking CI/CMDB records.
2. Okta (user directory, group membership, app assignments)
Browse the Okta admin console. User profiles, group memberships, app assignment status, and MFA enrollment became queryable.
3. Jira (engineering tickets, sprint status, linked incidents)
Browse Jira's web UI. Project boards, issue search, and linked tickets became accessible via MCP.
With all three connected to Claude, the IT lead could resolve tickets in a single conversation:
Access request tickets:
"User jane.doe@company.com is requesting access to Salesforce. What groups is she in, does her manager have Salesforce access, and is there a pending Jira task for this?"
Claude checks Okta group membership, compares against manager's assignments, and searches Jira for related provisioning tasks. Full context in 10 seconds.
Incident investigation:
"We have 5 new tickets about VPN connectivity. Are there related incidents in ServiceNow this week? Any Jira issues tagged with VPN in the infrastructure project?"
Claude correlates across systems, identifies a known issue, and surfaces the relevant knowledge article.
Onboarding checklists:
"New hire starting Monday: Alex Rivera, Engineering. What's their Okta status, are all standard apps provisioned, and is the onboarding ticket in ServiceNow updated?"
Claude pulls user state, verifies app assignments against the engineering template, and checks ticket completion.
Total time from zero to working: under 5 minutes.
No API tokens to manage manually. No custom ITSM integrations to maintain. Auth captured from existing browser sessions.
IT work is inherently cross-system. A single ticket touches identity (Okta), service management (ServiceNow), and engineering (Jira). These systems have APIs but building integrations between them is a multi-sprint project. MCP servers give AI direct query access without building connectors.
The IT manager's take: "My analysts used to spend 80% of their time finding information and 20% actually solving problems. Now those numbers are flipped."
Create your ServiceNow MCP server in 60 seconds.
Try with ServiceNow →{
"mcpServers": {
"servicenow": {
"url": "https://datafaucet.dev/api/mcp/YOUR_SERVER_ID/sse"
}
}
}Replace YOUR_SERVER_ID with the ID from your DataFaucet dashboard after creating your ServiceNow server.
Point DataFaucet at ServiceNow and get a working server in 60 seconds.
Create ServiceNow server free →After creating, add to Claude Desktop:
"servicenow": {
"url": "https://datafaucet.dev/api/mcp/YOUR_ID/sse"
}Free plan includes 3 servers. Upgrade to Pro for unlimited →
Turn Okta into an MCP server. AI agents can query users, groups, app assignments, and auth policies from Claude, Cursor, or Windsurf.
Create a ServiceNow MCP server that lets Claude, Cursor, and Codex manage incidents, query the CMDB, and automate ITSM workflows. No integration code needed.
A startup connected Stripe, Linear, Slack, Vercel, and PostHog to AI via MCP. Standup prep went from 15 minutes to one prompt.
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