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Agentic AI systems have the potential to work together, but not yet at scale. This episode breaks down two emerging standards — Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication.
Tech with Tim on MSN3h
How to Build a Local AI Agent With Python (Ollama, LangChain & RAG)I'll be showing you how to build local AI agents using Python. We'll be using Ollama, LangChain, and something called ...
3h
Interesting Engineering on MSNNVIDIA unveils world’s first long-context AI that serves 32x more users liveNVIDIA has unveiled a powerful new parallelism technique that could radically improve how AI models operate on massive ...
Discover how n8n’s AI-powered Model Context Protocol (MCP) simplifies workflow automation, reduces errors, and unlocks new ...
This new era doesn’t require every PM to become a software engineer, but it does require a higher level of technical fluency.
Microsoft has added preview support for the Model Context Protocol (MCP) to its Azure AI Foundry Agent Service, aiming for ...
This integration tax is not unique: It’s the hidden cost of today’s fragmented AI landscape. Anthropic’s Model Context Protocol (MCP) is one of the first attempts to fill this gap.
Whether you're a Java programmer curious about how to integrate LLM-based applications into your local data stores, or a Spring Boot developer who wants to integrate services with real-time language ...
I have developed a local MCP server which performs retrieval to an ElasticSearch database using hybrid search. The MCP server works fine when adding it to Claude Desktop, or when running the MCP ...
Model Context Protocol (MCP) is an open standard (introduced in late 2024 by Anthropic) that standardizes how AI models connect to data sources and tools. This repository aims to provide a clear, ...
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