agent-framework-core
Microsoft Agent Framework for building AI Agents with Python. This is the core package that has all the core abstractions and implementations.
Decision gist · record as of 2026-08-14
Yes. Active, well-maintained framework with strong community adoption (12803 stars, top 5000 PyPI packages). MIT license, low install friction, no known vulnerabilities, and comprehensive multi-agent orchestration capabilities. Install if you need to build or coordinate AI agents; skip if you only need direct LLM chat without agent abstractions.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10+.
- Requires LLM provider credentials (e.g., OPENAI_API_KEY) set via environment variables or configuration.
- Low friction installation with a pure-Python wheel.
License · maintenance · safety
permissive license (permissive) — MIT license (permissive) allows unrestricted use, modification, and distribution in commercial and private projects with minimal obligations.
last release 2026-08-14 (0 days) · last repo commit 2026-08-14 · 12,803 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 2,281,417 downloads/mo, #3,165 on PyPI
Alternatives
Verify before relying
pip install agent-framework-core
import asyncio
from agent_framework_core import Agent
agent = Agent(
instructions="You are a helpful assistant."
)
result = asyncio.run(agent.run("Hello"))
print(result)- Which LLM providers (OpenAI, Foundry, Anthropic) are included in core versus optional integration packages
- Performance characteristics and latency overhead of the orchestration layer
- Whether distributed execution requires additional infrastructure or dependencies beyond the core package
What it is and what it does
Agent Framework Core is Microsoft's Python library for building and orchestrating AI agents powered by large language models. It provides abstractions for creating individual agents with custom instructions and tools, then composing them into multi-agent systems using patterns like sequential workflows, concurrent execution, group chat, and handoff protocols. The framework handles LLM communication, function calling, message routing, and telemetry.
You use it by instantiating agents with configuration, optionally attaching custom Python functions as tools, then either running agents directly or coordinating multiple agents through orchestration patterns. It supports both in-process and distributed execution, multimodal inputs (text and vision), and integrates with opentelemetry-api for observability. Core dependencies include msgspec, pydantic, typing-extensions, python-dotenv, and opentelemetry-api.
Use it for
- Build a single agent with custom tools to answer questions and call functions on behalf of users.
- Orchestrate multiple agents in sequence to iteratively refine outputs based on feedback.
- Run multiple specialized agents concurrently to parallelize work on independent subtasks.
- Implement group chat where multiple agents collaborate and discuss to reach consensus.
- Deploy agents in distributed environments for scalable, fault-tolerant multi-agent applications.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Active, well-maintained framework with strong community adoption (12803 stars, top 5000 PyPI packages). MIT license, low install friction, no known vulnerabilities, and comprehensive multi-agent orchestration capabilities. Install if you need to build or coordinate AI agents; skip if you only need direct LLM chat without agent abstractions.
Install
agent-framework-core on PyPI
Before you install
Low friction installation with a pure-Python wheel. Active maintenance with recent release and strong community signal (12803 stars). Supports Python 3.10 through 3.14.
Requires Python 3.10+. Requires LLM provider credentials (e.g., OPENAI_API_KEY) set via environment variables or configuration.
License in practice
MIT license (permissive) allows unrestricted use, modification, and distribution in commercial and private projects with minimal obligations.
Quickstart
pip install agent-framework-core
import asyncio
from agent_framework_core import Agent
agent = Agent(
instructions="You are a helpful assistant."
)
result = asyncio.run(agent.run("Hello"))
print(result)Verify before relying
- Which LLM providers (OpenAI, Foundry, Anthropic) are included in core versus optional integration packages
- Performance characteristics and latency overhead of the orchestration layer
- Whether distributed execution requires additional infrastructure or dependencies beyond the core package
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 5 packagesmsgspectyping-extensionspydanticpython-dotenvopentelemetry-api |
| Maintenance | Actively maintained 0 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 2,281,417 / month, #3,165 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended 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_core-1.14.0-py3-none-any.whl
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See also agent-framework · agent-framework-orchestrations · ai-parrot · marvin · semantic-kernel · phidata · agent-framework-foundry-local · agent-framework-claude · agent-framework-ollama · agent-framework-anthropic