🚀 PagerDuty AI Agent
@cnoe-io
About 🚀 PagerDuty AI Agent
PagerDuty AI Agent powered by 1st Party MCP Server using OpenAPI Codegen, LangGraph and LangChain MCP Adapters. Agent is exposed on various agent transport protocols (AGNTCY ACP, Google A2A, MCP Server)Agent for PagerDuty
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"agent-pagerduty": {
"command": "docker",
"args": [
"pull",
"ghcr.io/cnoe-io/agent-pagerduty:a2a-latest"
]
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is 🚀 PagerDuty AI Agent?
An LLM-powered agent built using the LangGraph ReAct Agent workflow and MCP tools, connecting to the PagerDuty API. It supports both ACP and A2A protocols for flexible integration with external user clients, and enforces PagerDuty API token-based authentication.
How to use 🚀 PagerDuty AI Agent?
Configure a .env file with your LLM provider details and a PagerDuty API key. Pull the Docker image from ghcr.io/cnoe-io/agent-pagerduty:a2a-latest and run it on port 8000, then use the agent-chat-cli to interact. Alternatively, clone the repo and run make run-a2a for local development.
Key features of 🚀 PagerDuty AI Agent
- LangGraph + LangChain MCP Adapter for agent orchestration
- Azure OpenAI GPT-4 as the LLM backend
- Multi-protocol support (ACP and A2A)
- Comprehensive PagerDuty API coverage (incidents, services, schedules, teams, users, escalation policies)
- Secure API token-based authentication
Use cases of 🚀 PagerDuty AI Agent
- List, create, update, and resolve incidents through conversational queries
- View and manage services and their statuses
- Query schedules, teams, users, and escalation policies
- Integrate into multi-agent workflows via either ACP or A2A protocol
FAQ from 🚀 PagerDuty AI Agent
What dependencies are required?
Python 3.13+, Poetry 2.1.1+, and Docker are required. An LLM provider (Azure OpenAI in the example) and a valid PagerDuty API key are needed.
How is authentication handled?
The agent uses a PagerDuty API key set in the PAGERDUTY_API_KEY environment variable. The key is passed to the PagerDuty API for all operations.
What protocols does it support?
It supports both the ACP (AGNTCY) and A2A (Google) protocols. ACP is considered legacy; A2A is the primary mode.
Where does data live?
All data resides in the PagerDuty system. The agent acts as a client, making API calls to https://api.pagerduty.com – no local storage of PagerDuty data.
Are there any known limitations?
The README does not mention specific limits beyond requiring network access to the PagerDuty API and the chosen LLM provider.
More AI & Agents MCP servers
Just Prompt - A lightweight MCP server for LLM providers
dislerjust-prompt is an MCP server that provides a unified interface to top LLM providers (OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and Ollama)
欢迎来到 智言平台
Shy2593666979AgentChat 是一个基于 LLM 的智能体交流平台,内置默认 Agent 并支持用户自定义 Agent。通过多轮对话和任务协作,Agent 可以理解并协助完成复杂任务。项目集成 LangChain、Function Call、MCP 协议、RAG、Memory、HITL、Skill、Milvus 和 ElasticSearch 等技术,实现高效的知识检索与工具调用,使用 FastAPI 构建高性能后端服务。
Sequential Thinking Multi-Agent System (MAS)
FradSerAn advanced sequential thinking process using a Multi-Agent System (MAS) built with the Agno framework and served via MCP.
1MCP - One MCP Server for All
1mcp-appA unified Model Context Protocol server implementation that aggregates multiple MCP servers into one.
Web Agent Protocol
OTA-Tech-AI🌐Web Agent Protocol (WAP) - Record and replay user interactions in the browser with MCP support
Comments