azure-ai-agentserver-core

What it is and what it does

Azure AI Agent Server Core is a Python framework for hosting containerized Azure AI agents. It abstracts away the operational plumbing — HTTP serving via Hypercorn on a configurable port, health readiness probes, graceful shutdown with request draining, and automatic OpenTelemetry tracing with Azure Monitor and OTLP export — so that protocol-specific packages can focus on endpoint logic. You subclass AgentServerHost, add your routes, and call run().

The package includes a durable state store (FoundryStateStore) for persisting agent session memory and per-user state, a @task decorator for building crash-resilient long-running agents that survive container restarts, and request context utilities for multi-user sessions that partition state by user ID while forwarding only the opaque call ID on outbound Foundry calls. Configuration is driven by environment variables (PORT, FOUNDRY_AGENT_NAME, APPLICATIONINSIGHTS_CONNECTION_STRING, OTEL_EXPORTER_OTLP_ENDPOINT, etc.), making it container-friendly.

Use it for

• Build a containerized agent that handles HTTP requests, exports traces to Azure Monitor, and serves on a configurable port with health probes.
• Implement multi-user agent sessions where each request carries user identity and call context, with state partitioned per user.
• Create a crash-resilient agent using the @task decorator that persists state across container restarts and redeployments.
• Set up graceful shutdown for an agent container that drains in-flight requests before exiting with a default 30 s timeout.
• Store agent session memory, conversation checkpoints, and per-user preferences in a durable state store with optimistic concurrency.

Worth the install?

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Install

azure-ai-agentserver-core on PyPI

Before you install

Low install friction with a pure-Python wheel. Active maintenance — released 8 days ago with recent commits. Requires Python 3.10 or later and brings 9 runtime dependencies including starlette, hypercorn, and OpenTelemetry libraries.

Requires Python 3.10 or later. Optional azure-identity package needed for DefaultAzureCredential; optional gRPC extra for OTLP/gRPC protocol support.

License in practice

MIT license (permissive) — you can use, modify, and distribute this package freely with minimal restrictions, making it suitable for both open-source and commercial projects.

Quickstart

pip install azure-ai-agentserver-core

from azure.ai.agentserver.core import AgentServerHost
from starlette.responses import JSONResponse
from starlette.routing import Route

class MyAgent(AgentServerHost):
    def __init__(self, **kwargs):
        routes = [Route("/my-endpoint", self._handle, methods=["POST"])]
        super().__init__(routes=routes, **kwargs)
    
    async def _handle(self, request):
        return JSONResponse({"status": "ok"})

app = MyAgent()
app.run()

Package facts

Evidence: azure_ai_agentserver_core-2.0.0-py3-none-any.whl

Tags

More Application Frameworks packages

See also azure-ai-agentserver-agentframework · azure-ai-agentserver-invocations · azure-ai-agentserver-responses · agent-framework-foundry-hosting · azure-ai-projects · agent-framework · agent-framework-foundry · agent-framework-foundry-local · spotinst-agent · spotinst-agent-2

Further reading