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PagerDuty MCP Server

PagerDuty MCP Server

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github.com/wpfleger96AI & Agents8Updated 1d ago

About PagerDuty MCP Server

PagerDuty MCP Server exposes PagerDuty incident and operational data to LLMs through structured tools, with selected write actions for incident response. It supports request-header, API-token, and OAuth 2.0 PKCE authentication.

Key features

  1. 01Query incidents, services, teams, and users
  2. 02Inspect schedules and on-call entries
  3. 03Acknowledge and resolve incidents
  4. 04Add notes to incidents
  5. 05Filter response fields to reduce context

Use cases

  1. 01Check incidents assigned to the current user
  2. 02Review upcoming on-call schedules
  3. 03Record investigation progress on an incident

MCP support

It acts as an MCP server, exposing PagerDuty resources and incident actions as tools for MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

PagerDuty MCP Server

A server that exposes PagerDuty API functionality to LLMs. This server is designed to be used programmatically, with structured inputs and outputs.

PagerDuty Server MCP server

PyPI Downloads Python Versions GitHub Contributors Lines of Code PyPI version License

Overview

The PagerDuty MCP Server provides a set of tools for interacting with the PagerDuty API. These tools are designed to be used by LLMs to perform various operations on PagerDuty resources such as incidents, services, teams, and users.

Getting Started

  1. Initialize your local Python environment:
cd pagerduty-mcp-server
brew install uv
uv sync
  1. Configure authentication (see Authentication below).

Authentication

Priority: X-PagerDuty-Token HTTP header > PAGERDUTY_API_TOKEN environment variable > OAuth 2.0 PKCE

Option 1: X-PagerDuty-Token Header (Platform Integration)

When running as part of a platform that injects per-request credentials, the server reads the X-PagerDuty-Token HTTP header. This takes highest priority and does not require any local configuration.

Option 2: API Token (Recommended for Most Users)

Set the PAGERDUTY_API_TOKEN environment variable, or add it to a .env file in the project root. The server will automatically load environment variables from the .env file if present.

Environment variable:

export PAGERDUTY_API_TOKEN=your_api_token_here

.env file (recommended):

echo "PAGERDUTY_API_TOKEN=your_api_token_here" > .env
Option 3: OAuth 2.0 PKCE (Local Interactive Use)

OAuth is available for local standalone usage. It opens a browser for authentication and stores tokens securely in the OS keyring. OAuth is opt-in — it only activates when PAGERDUTY_CLIENT_ID is set and no API token is present.

Setup:

  1. Register a PagerDuty OAuth application at Integrations → Developer Tools → My Apps.
  2. Set the required scope to read write.
  3. Set the redirect URI to http://localhost:5173/oauth/pagerduty (default port).
  4. Set the PAGERDUTY_CLIENT_ID environment variable to your application's client ID.

Optional configuration:

  • Set PAGERDUTY_CLIENT_SECRET to enable token refresh (confidential client).
  • Set PAGERDUTY_OAUTH_CALLBACK_PORT to override the default callback port (5173).

Usage

Claude/Cursor
{
  "mcpServers": {
    "pagerduty-mcp-server": {
      "command": "uvx",
      "args": ["pagerduty-mcp-server"],
      "env": {
          "PAGERDUTY_API_TOKEN": "<PAGERDUTY_API_TOKEN>"
      }
    }
  }
}
As Standalone Server
uv run pagerduty-mcp-server

Available Tools

Read Tools
  • get_escalation_policies — List or get details for escalation policies
  • get_incidents — List or get details for incidents (supports filtering by status, urgency, service, team, and time range)
  • get_oncalls — List on-call entries for a time range
  • get_schedules — List or get details for schedules
  • get_services — List or get details for services
  • get_teams — List or get details for teams
  • get_users — List or get details for users
  • list_users_oncall — List users on call for a specific schedule
  • build_user_context — Build a context object for the current authenticated user
Write Tools
  • acknowledge_incident — Acknowledge an incident (signals active investigation)
  • resolve_incident — Resolve an incident (stops further escalations)
  • add_incident_note — Add a note to an incident (for recording investigation progress or context)

The include Parameter

Most read tools accept an optional include parameter — a list of field names to return. When specified, only those fields are included in each response object, which reduces token usage in LLM contexts.

# Return only id, title, and status for each incident
get_incidents(include=["id", "title", "status"])

# Return only id and name for each service
get_services(include=["id", "name"])

See the tool documentation for the full list of available fields per tool.

Response Format

All API responses follow a consistent format:

{
  "metadata": {
    "count": "<int>",
    "description": "<str>"
  },
  "<resource_type>": [
    {
      "...": "..."
    }
  ],
  "error": {
    "message": "<str>",
    "code": "<str>"
  }
}

The error field is only present when an error occurs. Resource names in responses are always pluralized for consistency, even when a single item is returned.

Error Handling

When an error occurs, the response will include an error object with the following structure:

{
  "metadata": {
    "count": 0,
    "description": "Error occurred while processing request"
  },
  "error": {
    "message": "Invalid user ID provided",
    "code": "INVALID_USER_ID"
  }
}

Common error scenarios include:

  • Invalid resource IDs (e.g., user_id, team_id, service_id)
  • Missing required parameters
  • Invalid parameter values
  • API request failures
  • Response processing errors
Parameter Validation
  • All ID values (single-ID parameters and list filters such as team_ids) must contain only ASCII letters and digits; any other value returns an error
  • Date parameters must be valid ISO8601 timestamps
  • List parameters (e.g., statuses, team_ids) must contain valid values
  • In ID list filters, surrounding whitespace is stripped and blank IDs are ignored
  • Required parameters cannot be None or empty strings
  • For statuses in get_incidents, only triggered, acknowledged, and resolved are valid values
  • For urgency in incidents, only high and low are valid values
  • The limit parameter can be used to restrict the number of results returned by list operations
Rate Limiting and Pagination
  • The server respects PagerDuty's rate limits
  • The server automatically handles pagination for you
  • The limit parameter can be used to control the number of results returned by list operations
  • If no limit is specified, the server will return up to pagerduty_mcp_server.utils.RESPONSE_LIMIT results by default

User Context

Many functions accept a current_user_context parameter (defaults to True) which automatically filters results based on this context. When current_user_context is True, you cannot use certain filter parameters as they would conflict with the automatic filtering:

  • For incidents:
    • team_ids and service_ids cannot be used with current_user_context=True
  • For services:
    • team_ids cannot be used with current_user_context=True
  • For escalation policies:
    • user_ids and team_ids cannot be used with current_user_context=True
  • For users:
    • team_ids cannot be used with current_user_context=True
  • For on-calls:
    • user_ids and escalation_policy_ids cannot be used with current_user_context=True
    • schedule_ids can still be used to filter by specific schedules
    • The query will show on-calls for the escalation policies the current user is a target of
    • If the current user is not a target of any escalation policy and no schedule_ids are given, the tool returns an error; use current_user_context=False with explicit filters instead

Development

Running Tests

The test suite includes both unit tests and integration tests. Integration tests require a real connection to the PagerDuty API, while unit tests can run without API access.

The pytest-cov args are optional, use them to include a test coverage report in the output.

To run all tests (integration tests will be automatically skipped if PAGERDUTY_API_TOKEN is not set):

uv run pytest [--cov=src --cov-report=term-missing]

To run only unit tests (no API token required):

uv run pytest -m unit [--cov=src --cov-report=term-missing]

To run only integration tests (requires PAGERDUTY_API_TOKEN set in environment):

uv run pytest -m integration [--cov=src --cov-report=term-missing]

To run only tests related to a specific submodule:

uv run pytest -m <client|escalation_policies|...> [--cov=src --cov-report=term-missing]
Debug Server with MCP Inspector
npx @modelcontextprotocol/inspector uv run pagerduty-mcp-server
Documentation

Tool Documentation - Detailed information about available tools including parameters, return types, and example queries

Conventions
  • All API responses follow the standard format with metadata, resource list, and optional error
  • Resource names in responses are always pluralized for consistency
  • All functions that return a single item still return a list with one element
  • Error responses include both a message and a code
  • All timestamps are in ISO8601 format
  • Tests are marked with pytest markers to indicate their type (unit/integration) and the resource they test (incidents, teams, etc.)
Example Queries
  • Are there any incidents assigned to me currently in pagerduty?
  • Do I have any upcoming on call schedule in next 2 weeks?
  • Who else is a member of the personalization team?

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