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.
@cnoe-io
Basic information
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
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"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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.
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.
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.
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.
It supports both the ACP (AGNTCY) and A2A (Google) protocols. ACP is considered legacy; A2A is the primary mode.
All data resides in the PagerDuty system. The agent acts as a client, making API calls to `https://api.pagerduty.com` β no local storage of PagerDuty data.
The README does not mention specific limits beyond requiring network access to the PagerDuty API and the chosen LLM provider.

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