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    Pagerduty Mcp Server

    PagerDuty MCP Server for LLM Agent Integration

    7 stars
    Python
    Updated Jul 25, 2025

    Table of Contents

    • Overview
    • Getting Started
    • Usage
    • As Goose Extension (Desktop)
    • As Goose Extension (CLI)
    • Claude/Cursor
    • As Standalone Server
    • Response Format
    • Error Handling
    • Parameter Validation
    • Rate Limiting and Pagination
    • User Context
    • Development
    • Running Tests
    • Debug Server with MCP Inspector
    • Documentation
    • Conventions
    • Example Queries

    Table of Contents

    • Overview
    • Getting Started
    • Usage
    • As Goose Extension (Desktop)
    • As Goose Extension (CLI)
    • Claude/Cursor
    • As Standalone Server
    • Response Format
    • Error Handling
    • Parameter Validation
    • Rate Limiting and Pagination
    • User Context
    • Development
    • Running Tests
    • Debug Server with MCP Inspector
    • Documentation
    • Conventions
    • Example Queries

    Documentation

    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.

    PyPI Downloads

    Python Versions

    GitHub Contributors

    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:

    sh
    cd pagerduty-mcp-server
    brew install uv
    uv sync

    2. The PagerDuty MCP Server requires a PagerDuty API token. You can provide this in two ways:

    Option 1: Environment Variable

    bash
    export PAGERDUTY_API_TOKEN=your_api_token_here

    Option 2: .env File (Recommended)

    Create a .env file in the project root:

    bash
    echo "PAGERDUTY_API_TOKEN=your_api_token_here" > .env

    The server will automatically load environment variables from the .env file if present.

    Usage

    As Goose Extension (Desktop)

    In Goose:

    1. Go to Settings > Advanced Settings > Extensions > Add custom extension.

    2. Give the extension a name (e.g. pagerduty-mcp-server).

    3. Set Type to StandardIO.

    4. Enter the following in the Command field:

    bash
    uvx pagerduty-mcp-server

    5. Click Save.

    4. Enable the extension and confirm that Goose identifies your tools.

    As Goose Extension (CLI)

    yaml
    pagerduty:
        args:
          - pagerduty-mcp-server
        bundled: null
        cmd: uvx
        description: ''
        enabled: true
        env_keys:
          - PAGERDUTY_API_TOKEN
        envs: {}
        name: pagerduty
        timeout: 300
        type: stdio

    Claude/Cursor

    json
    {
      "mcpServers": {
        "pagerduty-mcp-server": {
          "command": "uvx",
          "args": ["pagerduty-mcp-server"],
          "env": {
              "PAGERDUTY_API_TOKEN": 
          }
        }
      }
    }

    As Standalone Server

    sh
    uv run path/to/repo/pagerduty-mcp-server/.venv/bin/pagerduty-mcp-server

    Response Format

    All API responses follow a consistent format:

    json
    {
      "metadata": {
        "count": ,  // Number of results
        "description": ""  // A short summary of the results
      },
      : [ // Always pluralized for consistency, even if one result is returned
        {
          ...
        },
        ...
      ],
      "error": {  // Only present if there's an error
        "message": "",  // Human-readable error description
        "code": ""  // Machine-readable error code
      }
    }

    Error Handling

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

    json
    {
      "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 parameters must be valid PagerDuty resource IDs
    • Date parameters must be valid ISO8601 timestamps
    • List parameters (e.g., statuses, team_ids) must contain valid values
    • Invalid values in list parameters will be ignored
    • Required parameters cannot be None or empty strings
    • For statuses in list_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 all resource types:
    • user_ids cannot be used with current_user_context=True
    • 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:
    • team_ids cannot be used with current_user_context=True
    • For on-calls:
    • user_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 all escalation policies associated with the current user's teams
    • This is useful for answering questions like "who is currently on-call for my team?"
    • The current user's ID is not used as a filter, so you'll see all team members who are on-call

    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):

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

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

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

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

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

    To run only parser tests:

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

    To run only tests related to a specific submodule:

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

    Debug Server with MCP Inspector

    bash
    npx @modelcontextprotocol/inspector uv run path/to/repo/pagerduty-mcp-server/.venv/bin/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), the resource they test (incidents, teams, etc.), and whether they test parsing functionality ("parsers" marker)

    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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