Building Advanced MCP (Model Context Protocol) Agents with Multi-Agent Coordination, Context Awareness, and Gemini Integration

[ad_1] class MCPAgent: “””Advanced MCP Agent with evolved capabilities – Jupyter Compatible””” def __init__(self, agent_id: str, role: AgentRole, api_key: str = None): self.agent_id = agent_id self.role = role self.api_key = api_key self.memory = [] self.context = AgentContext( agent_id=agent_id, role=role, capabilities=self._init_capabilities(), memory=[], tools=self._init_tools() ) self.model = None if GEMINI_AVAILABLE and api_key: try: genai.configure(api_key=api_key) self.model = genai.GenerativeModel(‘gemini-pro’)…

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Zhipu AI Unveils ComputerRL: An AI Framework Scaling End-to-End Reinforcement Learning for Computer Use Agents

[ad_1] In the rapidly evolving landscape of AI-driven automation, Zhipu AI has introduced ComputerRL, a groundbreaking framework designed to empower agents with the ability to navigate and manipulate complex digital workspaces. This innovation addresses a core challenge in AI agent development: the disconnect between computer agents and human-designed graphical user interfaces (GUIs). By integrating programmatic…

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Nebius AI Advances Open-Weight LLMs Through Reinforcement Learning for Capable SWE Agents

[ad_1] The landscape of software engineering automation is evolving rapidly, driven by advances in Large Language Models (LLMs). However, most approaches to training capable agents rely on proprietary models or costly teacher-based methods, leaving open-weight LLMs with limited capabilities in real-world scenarios. A team of researchers from Nebius AI and Humanoid introduced a reinforcement learning…

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FAQs: Everything You Need to Know About AI Agents in 2025

[ad_1] TL;DR Definition: An AI agent is an LLM-driven system that perceives, plans, uses tools, acts inside software environments, and maintains state to reach goals with minimal supervision. Maturity in 2025: Reliable on narrow, well-instrumented workflows; improving rapidly on computer use (desktop/web) and multi-step enterprise tasks. What works best: High-volume, schema-bound processes (dev tooling, data…

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A Code Implementation to Build a Multi-Agent Research System with OpenAI Agents, Function Tools, Handoffs, and Session Memory

[ad_1] In this tutorial, we begin by showcasing the power of OpenAI Agents as the driving force behind our multi-agent research system. We set up our Colab environment with the OpenAI API key, installed the OpenAI Agents SDK, and then defined custom function tools, web_search, analyze_data, and save_research, to harness the agents’ capabilities. We instantiate…

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Inside OpenAI’s quest to make AI do anything for you | TechCrunch

[ad_1] Shortly after Hunter Lightman joined OpenAI as a researcher in 2022, he watched his colleagues launch ChatGPT, one of the fastest-growing products ever. Meanwhile, Lightman quietly worked on a team teaching OpenAI’s models to solve high school math competitions.  Today that team, known as MathGen, is considered instrumental to OpenAI’s industry-leading effort to create…

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