agent-framework-azure-ai
Azure AI Foundry integration for Microsoft Agent Framework.
Decision gist · record as of 2026-08-14
Yes, if you are building agents on Microsoft Agent Framework and need semantic memory backed by Azure. The package is actively maintained, has low install friction, and integrates cleanly with the broader Azure AI ecosystem. The beta status (1.0.0rc6) means the API may change before 1.0 stable, so pin the version in production. No known security vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later and valid Azure credentials configured for AIProjectClient.
- Low friction install with a pure Python wheel.
- Active maintenance with recent commits and a substantial repository.
License · maintenance · safety
permissive license (permissive) — MIT license permits commercial and private use with minimal restrictions, making it suitable for most projects.
last release 2026-03-30 (137 days) · last repo commit 2026-08-14 · 12,804 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 415,688 downloads/mo, #6,824 on PyPI
Alternatives
Verify before relying
pip install agent-framework-azure-ai --pre
from agent_framework_azure_ai import FoundryMemoryProvider
from azure_ai_projects import AIProjectClient
# Create memory store and provider
memory_provider = FoundryMemoryProvider(project_client)
# Attach to agent for automatic memory retrieval and updates- Whether the memory store automatically persists across application restarts or requires explicit save/load logic
- Performance characteristics when retrieving contextual memories from large conversation histories
- Whether configurable memory update delays can be tuned for real-time vs. batch scenarios
What it is and what it does
This package extends Microsoft Agent Framework with Azure AI Foundry memory integration, allowing agents to maintain semantic memories of user profiles and conversation context. It provides a FoundryMemoryProvider that automatically retrieves static memories on first interaction, searches for contextual memories based on ongoing conversations, and updates the memory store with new messages.
The package wraps several Azure AI dependencies (azure-ai-projects, azure-ai-agents, azure-ai-inference) and the core agent-framework components to create a turnkey memory layer. It is currently in beta (1.0.0rc6) and supports Python 3.10 through 3.14. The integration is designed for developers building conversational agents that need persistent, searchable memory without manual state management.
Use it for
- Building customer support agents that remember user preferences and past interactions across multiple sessions
- Creating personalized conversational AI that learns and recalls user context automatically during conversations
- Implementing multi-turn dialogue systems where agents need to reference earlier conversation topics without explicit prompting
- Developing agents that maintain user profiles and adapt behavior based on remembered preferences
- Prototyping agent memory features using Azure's managed memory infrastructure without building custom persistence
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building agents on Microsoft Agent Framework and need semantic memory backed by Azure.
The package is actively maintained, has low install friction, and integrates cleanly with the broader Azure AI ecosystem. The beta status (1.0.0rc6) means the API may change before 1.0 stable, so pin the version in production. No known security vulnerabilities.
Install
agent-framework-azure-ai on PyPI
Before you install
Low friction install with a pure Python wheel. Active maintenance with recent commits and a substantial repository. Still in beta (1.0.0rc6), so expect API surface changes before a stable release.
Requires Python 3.10 or later and valid Azure credentials configured for AIProjectClient.
License in practice
MIT license permits commercial and private use with minimal restrictions, making it suitable for most projects.
Quickstart
pip install agent-framework-azure-ai --pre
from agent_framework_azure_ai import FoundryMemoryProvider
from azure_ai_projects import AIProjectClient
# Create memory store and provider
memory_provider = FoundryMemoryProvider(project_client)
# Attach to agent for automatic memory retrieval and updatesVerify before relying
- Whether the memory store automatically persists across application restarts or requires explicit save/load logic
- Performance characteristics when retrieving contextual memories from large conversation histories
- Whether configurable memory update delays can be tuned for real-time vs. batch scenarios
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 7 packagesagent-framework-coreagent-framework-openaiazure-ai-projectsazure-ai-agentsazure-ai-inferenceazure-identityaiohttp |
| Maintenance | Actively maintained 137 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 415,688 / month, #6,824 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Typing :: Typed |
Evidence: agent_framework_azure_ai-1.0.0rc6-py3-none-any.whl
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See also agent-framework-azure-cosmos · agent-framework-foundry-local · agent-framework-mem0 · agent-framework-redis · agent-framework-azure-ai-search · semantic-kernel · hindsight-api-slim · agent-framework-foundry · langmem · agent-framework-azurefunctions