PagerDuty, Inc., a leader in AI-first operations management, has expanded its AI integration ecosystem to strengthen the capabilities of its PagerDuty Advance agents and AI platform. Through this development, the company aims to help organizations move closer to autonomous operations while managing the growing complexity of AI-driven software development.

As organizations accelerate development cycles and increasingly generate code using artificial intelligence, they face a new challenge: ensuring that the code does not break once deployed in production environments. To address this issue, PagerDuty has introduced more than 30 AI partners across 11 different categories on its AI integrations website. Moreover, the company has created an intuitive and searchable public directory that showcases integrations and agentic workflows.

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Through this directory, the PagerDuty Operations Cloud Platform and the PagerDuty Advance Site Reliability Engineer (SRE) Agent connect seamlessly with leading AI-native platforms and SaaS enterprise applications. As a result, organizations can better manage the complexities of AI operations while improving the reliability of their systems.

Strengthening Incident Management Across the Lifecycle

At the core of the expanded ecosystem is PagerDuty’s ability to transform operations across the entire incident management lifecycle. By ingesting rich observability telemetry, the AI ecosystem builds a self-reinforcing context flywheel. Consequently, this enables automated triage supported by deep operational insights.

For instance, PagerDuty’s SRE Agent can automatically correlate alerts, speed up root-cause analysis, and deliver more resilient operational outcomes. In addition, the ecosystem embeds operational intelligence directly into integrated development environments (IDEs). This allows developers and engineers to conduct pre-commit risk scoring, helping them identify potential issues before code is deployed.

Furthermore, this proactive approach helps prevent incidents from reaching production environments. For companies building AI-powered applications, the ecosystem also extends into large language model operations (LLMOps) and agent governance. At the same time, it enables agentic cloud operations by allowing direct communication between PagerDuty and cloud provider agents for automated remediation and self-healing infrastructure.

Building an Integrated Operational Layer for the AI Era

With this expansion, PagerDuty continues to position itself as a central intelligence and action platform for AI-driven operations. The company already supports more than 700 integrations. Now, it is expanding further into AI-focused segments such as agentic operations, coding agents, integrated development environments, and enterprise copilots.

Additionally, PagerDuty enhances interoperability through Model Context Protocol (MCP) integrations, enabling seamless connectivity between AI systems and operational platforms. These integrations work through three primary pathways: partners connecting to PagerDuty’s MCP Server to access service, team, and incident context; PagerDuty connecting to partner MCP servers for interoperability; and direct API integrations between partner platforms and PagerDuty.

When customers enable these integrations, the system strengthens the context flywheel. Over time, the platform learns from every incident, allowing teams to resolve issues faster and reduce the likelihood of future disruptions.

“Organizations are racing to adopt AI agents, but the real challenge is making them work together seamlessly in production environments,” said Jennifer Tejada, CEO and Chairperson of PagerDuty. “Our AI integration ecosystem solves this by connecting 30-plus AI partners directly into the operational workflows teams already rely on. This means faster incident resolution, reduced downtime, and the ability to prevent issues from impacting customers at all.”

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Strategic Partnerships Expand Ecosystem Capabilities

PagerDuty also highlighted several strategic partnerships that demonstrate the ecosystem’s practical benefits.

Through its collaboration with Anthropic, PagerDuty launched a plugin for Claude Code powered by MCP and listed it in the official Anthropic marketplace. This plugin analyzes uncommitted code changes against historical incident data, helping developers detect risky changes before deployment. In addition, the tool offers pre-commit risk scoring and a background agent that automatically investigates and summarizes incident context.

Meanwhile, PagerDuty’s partnership with Cursor introduces an MCP plugin available in the Cursor Marketplace. With a simple one-step installation, developers can access on-call schedules, service information, and incident history directly within the Cursor coding environment. When incidents occur, the platform can trigger automated agents to analyze logs and summarize potential root causes in real time.

In another collaboration, PagerDuty integrated with LangChain’s LangSmith platform to strengthen observability across the agent development lifecycle. The integration automatically triggers PagerDuty incidents when LangSmith detects issues such as error spikes, latency increases, or declining feedback scores. Additionally, both companies developed an Incident Responder agent template for LangSmith’s Agent Builder, enabling teams to deploy incident-response agents quickly.

“Our recent development work with PagerDuty demonstrates the power of an integrated AI ecosystem,” said Josh Ma, engineering lead at Cursor. “Between our native Automations integration and the PagerDuty plugin, developers now have multiple ways to access critical operational context and resolve incidents directly from their agentic coding environment.”

“LangSmith gives teams observability across the full agent development lifecycle to catch performance regressions fast,” said Harrison Chase, co-founder and CEO at LangChain. “The integration with PagerDuty closes the next gap: when LangSmith detects a critical issue, it triggers a PagerDuty incident through your existing workflows automatically. And with the Agent Builder Incident Responder template built on PagerDuty’s MCP server, teams can spin up an agent to improve incident response in minutes.”

Expanding the Future of AI Operations

Beyond these partnerships, PagerDuty’s ecosystem also includes agentic cloud operations integrations with AWS DevOps and Azure SRE environments. These integrations enable native communication between PagerDuty and cloud provider agents, allowing teams to share critical operational context and pave the way for automated remediation.

Additionally, the PagerDuty Incident Responder Custom Agent for GitHub embeds operational intelligence directly into GitHub Copilot. As a result, developers can query incident data and execute response actions without leaving their development workflows.

Together, these innovations reinforce PagerDuty’s mission to help organizations operate more resilient, AI-powered systems while reducing operational risk in increasingly complex digital environments.

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