PagerDuty MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add PagerDuty as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to PagerDuty. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in PagerDuty?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine PagerDuty tool responses with indexed documents for comprehensive, grounded answers. Connect 11 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the PagerDuty MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 11 tools from PagerDuty
Why Use LlamaIndex with the PagerDuty MCP Server
LlamaIndex provides unique advantages when paired with PagerDuty through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine PagerDuty tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain PagerDuty tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query PagerDuty, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what PagerDuty tools were called, what data was returned, and how it influenced the final answer
PagerDuty + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the PagerDuty MCP Server delivers measurable value.
Hybrid search: combine PagerDuty real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query PagerDuty to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying PagerDuty for fresh data
Analytical workflows: chain PagerDuty queries with LlamaIndex's data connectors to build multi-source analytical reports
PagerDuty MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect PagerDuty to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting PagerDuty to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpPagerDuty + LlamaIndex FAQ
Common questions about integrating PagerDuty MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect PagerDuty with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect PagerDuty to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.