watsonchua/singapore-resale-agent

Agents Compare

Welcome to Agents Compare, a project dedicated to comparing different agentic frameworks used for building AI agents and workflows.

Overview

This project evaluates and compares three popular agentic frameworks:

1. 1.MCP-Agents - A simple, composable framework to build agents using Model Context Protocol
2. 2.Smol-Agents - A lightweight agent framework by Hugging Face.
3. 3.LangGraph - A library for building stateful, multi-agent applications with LLMs

Purpose

The goal of this comparison is to understand the strengths, weaknesses, and unique features of each framework. This can help developers and researchers choose the appropriate framework for their specific use cases.

Frameworks

MCP-Agent

[MCP-Agent]https://github.com/lastmile-ai/mcp-agent)

Smol-Agents

Smol-Agents is a minimalist framework for building lightweight AI agents. It's designed for simplicity and ease of use.

LangGraph

LangGraph is part of the LangChain ecosystem that provides tools for building stateful, multi-agent workflows with LLMs. It allows for complex agent interactions through graph structures.

Comparison Criteria

This project evaluates these frameworks based on:

• —Ease of implementation
• —Performance
• —Flexibility
• —Documentation and community support
• —Use case suitability

Stay tuned for detailed comparison results and example implementations.