Can I acknowledge and resolve incidents directly from my AI agent?

Yes! Use the `update_incident` tool with the incident ID and your PagerDuty email. Set status to `acknowledged` or `resolved` to change the incident state instantly without opening the PagerDuty dashboard.

How do I find out who is on-call right now?

Run the `list_oncalls` tool. It returns every user currently on-call across all schedules and escalation levels, showing their name, escalation policy, and coverage window.

Can I create incidents programmatically for testing or escalation?

Absolutely. Use `create_incident` with your PagerDuty email, the target service ID, a descriptive title, and optionally set urgency to `high` or `low`. The incident will immediately trigger according to the service's escalation policy.

PagerDuty MCP Server for CrewAI 11 tools — connect in under 2 minutes

Name: PagerDuty
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 11 Tools Framework

Connect your CrewAI agents to PagerDuty through Vinkius, pass the Edge URL in the `mcps` parameter and every PagerDuty tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="PagerDuty Specialist",
    goal="Help users interact with PagerDuty effectively",
    backstory=(
        "You are an expert at leveraging PagerDuty tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in PagerDuty "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 11 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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High SecurityEnterprise-grade

IAMAccess control

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V8 IsolateSandboxed

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<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About PagerDuty MCP Server

Connect your PagerDuty account to any AI agent and take full control of incident management operations through natural conversation.

When paired with CrewAI, PagerDuty becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call PagerDuty tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Incident Management — List, create, acknowledge, and resolve incidents across all services
Service Monitoring — Browse all monitored services and inspect their configurations, integrations, and health status
User Management — List all team members, view individual profiles, contact methods, and notification rules
On-Call Visibility — See who is currently on-call across all schedules and escalation levels in real-time
Schedule Administration — Browse rotation schedules with their layers, handoff times, and coverage windows
Escalation Policies — Inspect escalation chains to understand how incidents route through teams

The PagerDuty MCP Server exposes 11 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect PagerDuty to CrewAI via MCP

Follow these steps to integrate the PagerDuty MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 11 tools from PagerDuty

Why Use CrewAI with the PagerDuty MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with PagerDuty through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

PagerDuty + CrewAI Use Cases

Practical scenarios where CrewAI combined with the PagerDuty MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries PagerDuty for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries PagerDuty, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain PagerDuty tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries PagerDuty against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

PagerDuty MCP Tools for CrewAI (11)

These 11 tools become available when you connect PagerDuty to CrewAI via MCP:

create_incident

Requires the From header email (your PagerDuty user email), service ID, and incident title. Create a new incident on a service

get_incident

Get detailed information about a specific incident

get_service

Get detailed configuration of a specific service

get_user

Get detailed information about a specific user

list_escalation_policies

List all escalation policies

list_incidents

Optionally filter by status: triggered, acknowledged, resolved. List incidents across all services

list_oncalls

List who is currently on-call across all schedules

list_schedules

List all on-call schedules

list_services

List all monitored services

list_users

List all users in the PagerDuty account

update_incident

Use to acknowledge, resolve, or reassign incidents programatically. Update an incident status (acknowledge, resolve, escalate)

Example Prompts for PagerDuty in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with PagerDuty immediately.

"Show me all triggered incidents right now."

"Who is on-call for the Platform team right now?"

"Acknowledge incident P8K2LMN and show me the service details."

Troubleshooting PagerDuty MCP Server with CrewAI

Common issues when connecting PagerDuty to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

PagerDuty + CrewAI FAQ

Common questions about integrating PagerDuty MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.