What can PagerDuty MCP Server do?

incident-list-and-filter-with-status-awareness, incident-acknowledgment-with-context-preservation, on-call-schedule-querying-with-time-aware-lookup, escalation-policy-trigger-with-validation, alert-acknowledgment-with-deduplication, incident-detail-enrichment-with-timeline-context, service-and-escalation-policy-metadata-lookup, mcp-protocol-tool-registration-and-schema-validation, api-authentication-and-token-management, mcp server for pagerduty incident management

PagerDuty MCP Server

MCP ServerFree

Manage PagerDuty incidents, alerts, and on-call schedules via MCP.

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10 capabilities

Best for: incident-list-and-filter-with-status-awareness, incident-acknowledgment-with-context-preservation, on-call-schedule-querying-with-time-aware-lookup
Type: MCP Server · Free
Score: 62/100
Best alternative: AWS MCP Servers
Agent-compatible: Yes — MCP protocol

Capabilities10 decomposed

incident-list-and-filter-with-status-awareness

Medium confidence

Retrieves incidents from PagerDuty API with real-time status filtering (triggered, acknowledged, resolved) and pagination support. Implements MCP tool protocol to expose PagerDuty's incident endpoint as a callable function, translating query parameters into REST API calls and normalizing response data into structured JSON for LLM consumption.

Solves for

Get a list of all active incidents across my organization right nowFilter incidents by status to see which ones need immediate attentionRetrieve incident details programmatically to feed into an LLM-based incident analysis workflowIntegrate incident data into an AI agent that makes decisions about escalation

Best for

DevOps teams building AI-powered incident dashboards

SREs automating incident triage with LLM agents

On-call engineers using Claude or other LLM clients with MCP support

Requires

PagerDuty API token with read access to incidents

MCP client that supports tool calling (Claude Desktop, Cline, etc.)

Network connectivity to PagerDuty API endpoints

Limitations

Pagination is manual — no built-in cursor iteration, requires multiple tool calls for large incident lists

Real-time filtering happens server-side via PagerDuty API; no local caching means latency depends on API response time

Limited to incidents accessible by the API token's service account permissions

What makes it unique

Exposes PagerDuty incident listing as an MCP tool rather than requiring direct API integration, allowing LLM agents to query incidents without writing HTTP code. Normalizes PagerDuty's REST response schema into a simplified JSON structure optimized for LLM token efficiency.

vs alternatives

Simpler than building custom incident integrations because it abstracts PagerDuty API authentication and response parsing into a single MCP tool call, reducing boilerplate in LLM agent code.

incident-acknowledgment-with-context-preservation

Medium confidence

Acknowledges incidents in PagerDuty by incident ID, optionally attaching context notes or metadata. Implements MCP tool that wraps PagerDuty's PATCH /incidents endpoint, preserving incident state while updating acknowledgment status and optionally adding notes for audit trails. Supports idempotent operations to prevent duplicate acknowledgments.

Solves for

Acknowledge an incident from an LLM agent without manual PagerDuty UI interactionAdd context or notes when acknowledging to document why an incident was acknowledgedPrevent duplicate acknowledgments when the same incident is processed multiple timesCreate an audit trail of AI-driven incident acknowledgments for compliance

Best for

Automated incident response workflows driven by LLM agents

Teams using Claude or other LLM clients to triage and acknowledge incidents

Organizations requiring audit trails of incident state changes

Requires

PagerDuty API token with write access to incidents

Valid incident ID from PagerDuty

MCP client with tool-calling capability

Limitations

Acknowledgment is user-scoped to the API token's service account; cannot acknowledge on behalf of specific on-call engineers

No rollback mechanism — acknowledged incidents cannot be automatically un-acknowledged if the agent makes an error

Notes are appended as incident timeline entries; no structured metadata field for machine-readable context

What makes it unique

Wraps PagerDuty's incident acknowledgment API as an idempotent MCP tool, allowing LLM agents to safely acknowledge incidents without risk of state conflicts. Preserves incident context (assigned user, escalation policy) while updating only the acknowledgment status.

vs alternatives

More reliable than manual incident acknowledgment because it's atomic and idempotent, whereas UI-based acknowledgment can race with other team members; integrates directly into LLM agent workflows without custom error handling.

on-call-schedule-querying-with-time-aware-lookup

Medium confidence

Queries PagerDuty on-call schedules to determine who is currently on-call or scheduled for future shifts. Implements MCP tool that calls PagerDuty's schedule endpoint with optional time range parameters, returning on-call user details and shift times. Supports querying multiple schedules and resolving escalation policies to their underlying on-call users.

Solves for

Find out who is on-call right now for a specific service or escalation policyCheck the on-call schedule for the next 7 days to plan incident responseResolve an escalation policy to the actual on-call engineer for context in incident analysisBuild an LLM agent that can answer 'who should I contact about this incident?'

Best for

On-call engineers building AI assistants that need to know shift coverage

Incident response teams automating escalation decisions based on schedule data

Organizations with complex escalation policies requiring schedule resolution

Requires

PagerDuty API token with read access to schedules

Schedule IDs or escalation policy IDs to query

Optional: timezone string (e.g., 'America/New_York') for accurate time-based queries

Limitations

Schedule data is point-in-time; no real-time updates if an on-call engineer manually changes their availability

Timezone handling depends on PagerDuty account configuration; queries must specify timezone or use account default

Cannot query historical on-call data beyond PagerDuty's retention window (typically 90 days)

What makes it unique

Exposes PagerDuty's schedule API as an MCP tool with time-aware querying, allowing LLM agents to resolve 'who is on-call?' questions without manual schedule lookups. Handles escalation policy resolution transparently, returning the actual on-call user rather than just policy metadata.

vs alternatives

More contextual than static on-call lists because it queries real-time schedule data and respects time ranges, enabling LLM agents to make decisions based on current shift coverage rather than stale information.

escalation-policy-trigger-with-validation

Medium confidence

Triggers escalation policies in PagerDuty to manually escalate incidents or create new incidents. Implements MCP tool that wraps PagerDuty's incident creation/escalation endpoint, validating escalation policy IDs and service associations before submission. Supports custom incident titles, descriptions, and urgency levels to provide context for escalated incidents.

Solves for

Manually escalate an incident to the next level in the escalation policy from an LLM agentCreate a new incident with a specific escalation policy when an automated system detects a critical issueTrigger an escalation with custom context (title, description, urgency) to ensure on-call engineers have full detailsBuild an LLM agent that can decide when to escalate and execute escalation automatically

Best for

Automated incident response systems that need to escalate based on AI-driven decisions

On-call teams using LLM agents to manage incident escalation workflows

Organizations automating escalation decisions based on incident severity or age

Requires

PagerDuty API token with write access to incidents

Valid escalation policy ID from PagerDuty

Service ID associated with the escalation policy

Limitations

Escalation is immediate and irreversible; no dry-run mode to preview escalation before execution

Escalation policy must be pre-configured in PagerDuty; MCP tool cannot create or modify policies

Cannot escalate to specific individuals — escalation follows the policy's defined levels and users

What makes it unique

Provides MCP-based escalation policy triggering with validation, allowing LLM agents to escalate incidents programmatically while ensuring policy IDs and service associations are correct before submission. Supports custom incident metadata (title, description, urgency) to provide context for escalated incidents.

vs alternatives

Safer than direct API calls because it validates escalation policy and service associations before execution, reducing the risk of escalating to the wrong policy. Integrates directly into LLM agent workflows without requiring custom validation logic.

alert-acknowledgment-with-deduplication

Medium confidence

Acknowledges individual alerts within PagerDuty incidents, supporting deduplication to prevent duplicate acknowledgments of the same alert. Implements MCP tool that wraps PagerDuty's alert acknowledgment endpoint, tracking alert IDs and timestamps to ensure idempotent operations. Supports batch acknowledgment of multiple alerts from a single incident.

Solves for

Acknowledge a specific alert within an incident without acknowledging the entire incidentPrevent duplicate acknowledgments when the same alert is processed multiple times by an LLM agentBatch acknowledge multiple alerts from a single incident in one operationCreate a detailed audit trail of which alerts were acknowledged and when

Best for

Teams managing incidents with multiple alerts that need granular acknowledgment

Automated alert processing systems that need to deduplicate acknowledgments

Organizations requiring detailed audit trails of alert state changes

Requires

PagerDuty API token with write access to incidents

Valid incident ID and alert ID(s) from PagerDuty

MCP client with tool-calling capability

Limitations

Alert deduplication is client-side; no server-side deduplication tracking, so duplicate calls within the same session may still process

Batch acknowledgment requires multiple alert IDs; no wildcard or pattern-based acknowledgment

Alert data is tied to incident lifecycle; acknowledged alerts are archived when incidents are resolved

What makes it unique

Provides granular alert-level acknowledgment as an MCP tool with client-side deduplication tracking, allowing LLM agents to acknowledge specific alerts within incidents rather than entire incidents. Supports batch operations for efficiency when processing multiple alerts.

vs alternatives

More granular than incident-level acknowledgment because it operates at the alert level, enabling LLM agents to acknowledge specific alerts while leaving others pending. Deduplication prevents accidental duplicate acknowledgments in retry scenarios.

incident-detail-enrichment-with-timeline-context

Medium confidence

Retrieves detailed incident information including full timeline, notes, and related alerts. Implements MCP tool that fetches incident details from PagerDuty's incident endpoint, aggregating timeline entries, notes, and alert data into a single enriched response. Supports filtering timeline entries by type (escalation, acknowledgment, note) to provide contextual information for LLM analysis.

Solves for

Get the full incident timeline to understand how an incident has evolvedRetrieve all notes and context added by team members during incident responseFetch related alerts to understand the root cause of an incidentBuild an LLM agent that can analyze incident history and provide recommendations

Best for

Incident analysis and post-mortem automation using LLM agents

Teams building AI-powered incident intelligence systems

On-call engineers using LLM assistants to understand incident context

Requires

PagerDuty API token with read access to incidents

Valid incident ID from PagerDuty

MCP client with sufficient context window for large timeline responses

Limitations

Timeline data is immutable after incident resolution; cannot retrieve historical changes to incident metadata

Large incidents with many timeline entries may exceed token limits in LLM context windows

Alert data is aggregated from PagerDuty's alert endpoint; no direct correlation to external monitoring systems

What makes it unique

Aggregates incident details, timeline, notes, and alerts into a single enriched response optimized for LLM consumption, rather than requiring separate API calls. Supports timeline filtering to reduce token usage by excluding irrelevant entries.

vs alternatives

More efficient than multiple API calls because it fetches all incident context in one operation, reducing latency and token overhead. Timeline filtering allows LLM agents to focus on relevant events without processing noise.

service-and-escalation-policy-metadata-lookup

Medium confidence

Queries PagerDuty to retrieve metadata about services and escalation policies, including policy levels, notification rules, and service integrations. Implements MCP tool that fetches service and escalation policy details from PagerDuty's API, normalizing response data for LLM consumption. Supports searching services by name or ID and resolving escalation policy structures.

Solves for

Look up a service by name to get its ID for incident creation or filteringUnderstand the structure of an escalation policy (levels, users, notification rules) for decision-makingFind all services managed by a specific team or escalation policyBuild an LLM agent that can recommend the correct escalation policy based on incident type

Best for

Teams building incident routing systems with LLM agents

On-call engineers using AI assistants to navigate service and escalation policy structures

Organizations automating incident creation with context-aware escalation policy selection

Requires

PagerDuty API token with read access to services and escalation policies

Service name or ID, or escalation policy ID to query

MCP client with tool-calling capability

Limitations

Metadata is static; changes to escalation policies or service configurations require re-querying

No caching mechanism in the MCP server; every query hits the PagerDuty API

Service search is limited to exact name matches or ID lookups; no fuzzy matching or regex support

What makes it unique

Exposes PagerDuty service and escalation policy metadata as MCP tools, allowing LLM agents to discover and understand organizational structure without manual lookups. Normalizes complex policy structures into simplified JSON for LLM token efficiency.

vs alternatives

More discoverable than hardcoded service/policy IDs because it allows LLM agents to search and resolve services by name, enabling dynamic incident routing based on organizational context.

mcp-protocol-tool-registration-and-schema-validation

Medium confidence

Registers PagerDuty operations as MCP tools with JSON Schema validation, ensuring that LLM clients can discover and call PagerDuty functions with type-safe parameters. Implements MCP server that exposes tools with standardized schemas (input/output types, required parameters, descriptions), enabling LLM clients to validate parameters before execution and provide autocomplete in IDE environments.

Solves for

Enable Claude, Cline, or other MCP clients to discover PagerDuty operations as callable toolsValidate incident IDs, service IDs, and other parameters before sending to PagerDuty APIProvide IDE autocomplete and type hints for PagerDuty operations in LLM agent codeEnsure LLM agents cannot accidentally call PagerDuty with malformed parameters

Best for

LLM client developers integrating PagerDuty into AI agents

Teams using Claude Desktop or Cline with MCP support

Organizations standardizing on MCP for tool integration across multiple services

Requires

MCP client that supports tool calling (Claude Desktop, Cline, etc.)

MCP server running and accessible to the client

PagerDuty API token configured in the MCP server environment

Limitations

Schema validation is client-side; malicious or non-compliant clients can bypass validation

Tool discovery is static; schema changes require server restart

No runtime parameter validation on the server side; relies on client-side schema enforcement

What makes it unique

Implements MCP protocol tool registration with JSON Schema validation, allowing LLM clients to discover and validate PagerDuty operations before execution. Provides standardized tool schemas that enable IDE autocomplete and type checking in LLM agent code.

vs alternatives

More reliable than direct API integration because schema validation prevents malformed requests from reaching PagerDuty, reducing error handling overhead in LLM agent code. MCP protocol enables tool discovery and reuse across multiple LLM clients.

api-authentication-and-token-management

Medium confidence

Manages PagerDuty API authentication using bearer tokens, handling token validation and error responses from the PagerDuty API. Implements secure token storage in environment variables or configuration files, with error handling for expired or invalid tokens. Supports token rotation and re-authentication without restarting the MCP server.

Solves for

Securely authenticate to PagerDuty API without exposing tokens in code or logsHandle authentication errors gracefully when tokens expire or are revokedRotate API tokens without restarting the MCP server or LLM clientEnsure that all PagerDuty API calls are authenticated with valid credentials

Best for

Teams deploying MCP servers in production environments

Organizations with strict security policies requiring token rotation

DevOps teams managing MCP server infrastructure

Requires

PagerDuty API token with appropriate permissions

Environment variable or configuration file to store token securely

Network connectivity to PagerDuty API endpoints

Limitations

Token storage is environment-dependent; no built-in encryption for tokens at rest

Token rotation requires manual configuration or external secret management system

No token expiration tracking; expired tokens will cause API errors until manually rotated

What makes it unique

Implements secure API token management for PagerDuty authentication, storing tokens in environment variables and validating them on each request. Provides error handling for expired or invalid tokens without exposing sensitive credentials in logs.

vs alternatives

More secure than hardcoding tokens because it uses environment variables and provides error handling for invalid tokens. Supports token rotation without restarting the MCP server, enabling credential updates in production environments.

mcp server for pagerduty incident management

Medium confidence

A community-driven MCP server specifically designed for managing PagerDuty incidents, providing tools for alert acknowledgment, incident listing, and on-call schedule queries, making it ideal for DevOps teams.

Solves for

best MCP server for incident managementMCP server for PagerDuty integrationcommunity MCP server for alert managementMCP server for on-call scheduling+1 more

Best for

DevOps teams

incident management

What makes it unique

This MCP server is tailored for PagerDuty, offering unique tools for incident management that are not found in generic MCP servers.

vs alternatives

It provides specialized features for PagerDuty users, unlike more generic incident management solutions.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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Best For

✓DevOps teams building AI-powered incident dashboards
✓SREs automating incident triage with LLM agents
✓On-call engineers using Claude or other LLM clients with MCP support
✓Automated incident response workflows driven by LLM agents
✓Teams using Claude or other LLM clients to triage and acknowledge incidents
✓Organizations requiring audit trails of incident state changes
✓On-call engineers building AI assistants that need to know shift coverage
✓Incident response teams automating escalation decisions based on schedule data

Known Limitations

⚠Pagination is manual — no built-in cursor iteration, requires multiple tool calls for large incident lists
⚠Real-time filtering happens server-side via PagerDuty API; no local caching means latency depends on API response time
⚠Limited to incidents accessible by the API token's service account permissions
⚠Acknowledgment is user-scoped to the API token's service account; cannot acknowledge on behalf of specific on-call engineers
⚠No rollback mechanism — acknowledged incidents cannot be automatically un-acknowledged if the agent makes an error
⚠Notes are appended as incident timeline entries; no structured metadata field for machine-readable context

Requirements

PagerDuty API token with read access to incidentsMCP client that supports tool calling (Claude Desktop, Cline, etc.)Network connectivity to PagerDuty API endpointsPagerDuty API token with write access to incidentsValid incident ID from PagerDutyMCP client with tool-calling capabilityPagerDuty API token with read access to schedulesSchedule IDs or escalation policy IDs to query

Input / Output

Accepts: query parameters (status, limit, offset, service_ids), incident_id (string), optional notes (string), schedule_id or escalation_policy_id (string), optional since (ISO 8601 timestamp), optional until (ISO 8601 timestamp), escalation_policy_id (string), service_id (string), optional title (string), optional description (string), optional urgency (high/low), incident_id (string), alert_id or alert_ids (string or array of strings), incident_id (string), optional include_timeline (boolean), optional timeline_type_filter (escalation/acknowledgment/note), service_id or service_name (string), or escalation_policy_id (string), JSON objects conforming to tool schemas, API token (string) provided via environment variable or configuration

Produces: JSON array of incident objects with id, title, status, urgency, service, assigned_via_escalation_policy, JSON object with updated incident status, acknowledgement timestamp, and timeline entry, JSON object with on-call user details (name, email, phone), shift start/end times, and schedule metadata, JSON object with newly created or escalated incident ID, status, escalation policy details, and assigned user, JSON object with acknowledged alert details, acknowledgment timestamp, and updated incident alert summary, JSON object with incident details, full timeline array, notes, alert summary, and escalation policy metadata, JSON object with service details (name, ID, integrations) or escalation policy structure (levels, users, notification rules), JSON objects conforming to tool output schemas, or error responses with validation details, Authentication headers for PagerDuty API requests, or error responses for invalid tokens

UnfragileRank

Adoption70%(25% weight)

Quality85%(25% weight)

Ecosystem42%(15% weight)

Match Graph25%(23% weight)

Freshness90%(12% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: MCP Server

10 capabilities

Visit PagerDuty MCP Server→

About

Community MCP server for PagerDuty incident management. Provides tools for listing and managing incidents, acknowledging alerts, querying on-call schedules, and triggering escalation policies.

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Capabilities10 decomposed

incident-list-and-filter-with-status-awareness

Medium confidence

Solves for

Best for

DevOps teams building AI-powered incident dashboards

SREs automating incident triage with LLM agents

On-call engineers using Claude or other LLM clients with MCP support

Requires

PagerDuty API token with read access to incidents

MCP client that supports tool calling (Claude Desktop, Cline, etc.)

Network connectivity to PagerDuty API endpoints

Limitations

Pagination is manual — no built-in cursor iteration, requires multiple tool calls for large incident lists

Real-time filtering happens server-side via PagerDuty API; no local caching means latency depends on API response time

Limited to incidents accessible by the API token's service account permissions

What makes it unique

vs alternatives

Simpler than building custom incident integrations because it abstracts PagerDuty API authentication and response parsing into a single MCP tool call, reducing boilerplate in LLM agent code.

incident-acknowledgment-with-context-preservation

Medium confidence

Solves for

Best for

Automated incident response workflows driven by LLM agents

Teams using Claude or other LLM clients to triage and acknowledge incidents

Organizations requiring audit trails of incident state changes

Requires

PagerDuty API token with write access to incidents

Valid incident ID from PagerDuty

MCP client with tool-calling capability

Limitations

Acknowledgment is user-scoped to the API token's service account; cannot acknowledge on behalf of specific on-call engineers

No rollback mechanism — acknowledged incidents cannot be automatically un-acknowledged if the agent makes an error

Notes are appended as incident timeline entries; no structured metadata field for machine-readable context

What makes it unique

vs alternatives

on-call-schedule-querying-with-time-aware-lookup

Medium confidence

Solves for

Best for

On-call engineers building AI assistants that need to know shift coverage

Incident response teams automating escalation decisions based on schedule data

Organizations with complex escalation policies requiring schedule resolution

Requires

PagerDuty API token with read access to schedules

Schedule IDs or escalation policy IDs to query

Optional: timezone string (e.g., 'America/New_York') for accurate time-based queries

Limitations

Schedule data is point-in-time; no real-time updates if an on-call engineer manually changes their availability

Timezone handling depends on PagerDuty account configuration; queries must specify timezone or use account default

Cannot query historical on-call data beyond PagerDuty's retention window (typically 90 days)

What makes it unique

vs alternatives

escalation-policy-trigger-with-validation

Medium confidence

Solves for

Best for

Automated incident response systems that need to escalate based on AI-driven decisions

On-call teams using LLM agents to manage incident escalation workflows

Organizations automating escalation decisions based on incident severity or age

Requires

PagerDuty API token with write access to incidents

Valid escalation policy ID from PagerDuty

Service ID associated with the escalation policy

Limitations

Escalation is immediate and irreversible; no dry-run mode to preview escalation before execution

Escalation policy must be pre-configured in PagerDuty; MCP tool cannot create or modify policies

Cannot escalate to specific individuals — escalation follows the policy's defined levels and users

What makes it unique

vs alternatives

alert-acknowledgment-with-deduplication

Medium confidence

Solves for

Best for

Teams managing incidents with multiple alerts that need granular acknowledgment

Automated alert processing systems that need to deduplicate acknowledgments

Organizations requiring detailed audit trails of alert state changes

Requires

PagerDuty API token with write access to incidents

Valid incident ID and alert ID(s) from PagerDuty

MCP client with tool-calling capability

Limitations

Alert deduplication is client-side; no server-side deduplication tracking, so duplicate calls within the same session may still process

Batch acknowledgment requires multiple alert IDs; no wildcard or pattern-based acknowledgment

Alert data is tied to incident lifecycle; acknowledged alerts are archived when incidents are resolved

What makes it unique

vs alternatives

incident-detail-enrichment-with-timeline-context

Medium confidence

Solves for

Best for

Incident analysis and post-mortem automation using LLM agents

Teams building AI-powered incident intelligence systems

On-call engineers using LLM assistants to understand incident context

Requires

PagerDuty API token with read access to incidents

Valid incident ID from PagerDuty

MCP client with sufficient context window for large timeline responses

Limitations

Timeline data is immutable after incident resolution; cannot retrieve historical changes to incident metadata

Large incidents with many timeline entries may exceed token limits in LLM context windows

Alert data is aggregated from PagerDuty's alert endpoint; no direct correlation to external monitoring systems

What makes it unique

vs alternatives

service-and-escalation-policy-metadata-lookup

Medium confidence

Solves for

Best for

Teams building incident routing systems with LLM agents

On-call engineers using AI assistants to navigate service and escalation policy structures

Organizations automating incident creation with context-aware escalation policy selection

Requires

PagerDuty API token with read access to services and escalation policies

Service name or ID, or escalation policy ID to query

MCP client with tool-calling capability

Limitations

Metadata is static; changes to escalation policies or service configurations require re-querying

No caching mechanism in the MCP server; every query hits the PagerDuty API

Service search is limited to exact name matches or ID lookups; no fuzzy matching or regex support

What makes it unique

vs alternatives

More discoverable than hardcoded service/policy IDs because it allows LLM agents to search and resolve services by name, enabling dynamic incident routing based on organizational context.

mcp-protocol-tool-registration-and-schema-validation

Medium confidence

Solves for

Best for

LLM client developers integrating PagerDuty into AI agents

Teams using Claude Desktop or Cline with MCP support

Organizations standardizing on MCP for tool integration across multiple services

Requires

MCP client that supports tool calling (Claude Desktop, Cline, etc.)

MCP server running and accessible to the client

PagerDuty API token configured in the MCP server environment

Limitations

Schema validation is client-side; malicious or non-compliant clients can bypass validation

Tool discovery is static; schema changes require server restart

No runtime parameter validation on the server side; relies on client-side schema enforcement

What makes it unique

vs alternatives

api-authentication-and-token-management

Medium confidence

Solves for

Best for

Teams deploying MCP servers in production environments

Organizations with strict security policies requiring token rotation

DevOps teams managing MCP server infrastructure

Requires

PagerDuty API token with appropriate permissions

Environment variable or configuration file to store token securely

Network connectivity to PagerDuty API endpoints

Limitations

Token storage is environment-dependent; no built-in encryption for tokens at rest

Token rotation requires manual configuration or external secret management system

No token expiration tracking; expired tokens will cause API errors until manually rotated

What makes it unique

vs alternatives

mcp server for pagerduty incident management

Medium confidence

Solves for

best MCP server for incident managementMCP server for PagerDuty integrationcommunity MCP server for alert managementMCP server for on-call scheduling+1 more

Best for

DevOps teams

incident management

What makes it unique

This MCP server is tailored for PagerDuty, offering unique tools for incident management that are not found in generic MCP servers.

vs alternatives

It provides specialized features for PagerDuty users, unlike more generic incident management solutions.

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

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AWS MCP Servers61MCP Server

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Compare →

Zapier MCP63MCP Server

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Compare →

Hugging Face MCP Server62MCP Server

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Atlassian Remote MCP Server63MCP Server

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See all alternatives to PagerDuty MCP Server→

PagerDuty MCP Server

Capabilities10 decomposed

incident-list-and-filter-with-status-awareness

incident-acknowledgment-with-context-preservation

on-call-schedule-querying-with-time-aware-lookup

escalation-policy-trigger-with-validation

alert-acknowledgment-with-deduplication

incident-detail-enrichment-with-timeline-context

service-and-escalation-policy-metadata-lookup

mcp-protocol-tool-registration-and-schema-validation

api-authentication-and-token-management

mcp server for pagerduty incident management

Related Artifactssharing capabilities

Pagerly

Cleric

Pagerly

ilert

Grafana

Rely.io

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

About

Categories

Alternatives to PagerDuty MCP Server

Are you the builder of PagerDuty MCP Server?

Get the weekly brief

Data Sources

PagerDuty MCP Server

Capabilities10 decomposed

incident-list-and-filter-with-status-awareness

incident-acknowledgment-with-context-preservation

on-call-schedule-querying-with-time-aware-lookup

escalation-policy-trigger-with-validation

alert-acknowledgment-with-deduplication

incident-detail-enrichment-with-timeline-context

service-and-escalation-policy-metadata-lookup

mcp-protocol-tool-registration-and-schema-validation

api-authentication-and-token-management

mcp server for pagerduty incident management

Related Artifactssharing capabilities

Pagerly

Cleric

Pagerly

ilert

Grafana

Rely.io

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