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Minimalist Python framework for building AI agents

Project description

AgentFlow

AgentFlow Logo

Tests Python 3.9+ License: MIT PyPI

The minimalist Python framework for building AI agents

AgentFlow is a production-ready framework that makes building AI agents simple, testable, and extensible. Inspired by FastAPI's philosophy of developer experience first.

🚀 Key Features

  • 🧪 Best-in-class Testing - MockModel + AgentTestClient (FastAPI-inspired)
  • 🔌 Native MCP Support - First Python framework with MCP integration
  • ⚡ Async-First - Built on asyncio for maximum performance
  • 🛡️ Production-Ready - Robust loop with JSON auto-repair, timeout protection, loop detection
  • 🔧 Tool Ecosystem - Mix local Python tools with MCP servers seamlessly
  • 📦 Multi-LLM - Ollama, OpenAI, Mistral support out of the box
  • 💾 Flexible Memory - InMemory and FileMemory with custom backend support

📥 Installation

pip install agentflow-ai==1.0.0

⚡ Quick Start

Basic Usage

import asyncio
from agentflow import Agent

async def main():
    agent = Agent(model="llama3")
    response = await agent.arun("What is Python?")
    print(response)

asyncio.run(main())

With Tools

agent = Agent(model="gpt-4o")

@agent.tool
def calculate(expression: str) -> float:
    """Evaluate a mathematical expression."""
    return eval(expression)

response = await agent.arun("What is 123 * 456?")

With MCP Servers

from agentflow.mcp import MCPClient

# Connect to filesystem server
async with MCPClient(
    transport="stdio",
    command=["npx", "@modelcontextprotocol/server-filesystem", "/tmp"]
) as mcp:
    await agent.add_mcp_tools(mcp)
    response = await agent.arun("List files in /tmp")

🧪 Testing (Killer Feature)

from agentflow.testing import MockModel, AgentTestClient

# Test without real LLM calls
model = MockModel(responses=["Hello! I'm an AI assistant."])
agent = Agent(model=model)
client = AgentTestClient(agent)

response = client.run("Hello")
client.assert_response_contains("Hello")
client.assert_tool_called("my_tool")

🆚 Why AgentFlow?

Feature AgentFlow LangChain CrewAI AutoGen
Easy Testing ✅ MockModel + TestClient
Native MCP ✅ First framework
Async-First Partial
Minimalist ✅ <700 LOC core
Production-Ready ✅ v1.0 Partial Partial

📚 Documentation & Examples

  • Documentation - Comprehensive guides and API reference
  • Examples - 8 complete examples covering all features

🏗️ Architecture

AgentFlow follows these principles:

  • Explicit > Magic - Clear APIs, no hidden behavior
  • Minimal by default - Start simple, add complexity when needed
  • Testable - Built-in mocking and assertion helpers
  • Async-first - Non-blocking I/O for performance

🔧 Requirements

  • Python 3.9+
  • httpx

📄 License

MIT License - see LICENSE file for details.

🙏 Credits

Created by Hamadi Chaabani

Inspired by:

  • FastAPI's developer experience
  • Anthropic's MCP vision
  • The Python async ecosystem

🔗 Ecosystem

⭐ Star History

If you find AgentFlow useful, please star it on GitHub!


AgentFlow v1.0 - Production-ready. Fully tested. Simply powerful.

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