Agentic

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I recently published a blog post on how to get started with the official A2A demo. In it we explored the capabilities of A2A and how it helps AI agents, potentially built with different frameworks…

As AI Agents and assistants become increasingly central to modern applications and experiences, the need for seamless, secure integration with external tools...

The Agent2Agent Protocol now has support from more than 50 major technology partners, including Atlassian, Salesforce, and Deloitte. This represents a transformation in AI agent communication methods.

Today we are launching MCP-Scan, a security scanner designed to protect your agentic systems from MCP-based security vulnerabilities, including Tool Poisoning Attacks and MCP Rug Pulls.

The Model Context Protocol (MCP) is quickly becoming the standard for integrating Tools 🛠️ with Agents 🤖 and Azure API Management is at the fore-front,...

Learn how Chain-of-Thought prompting improves AI reasoning by guiding models to explain their thought process. Discover its impact on LLM accuracy and complex tasks.

Contribute to philschmid/gemini-samples development by creating an account on GitHub.

Run a remote MCP server on Azure functions.

Azure API Management as AI Gateway to Remote MCP servers. - Azure-Samples/remote-mcp-apim-functions-python

Learn about the built-in authentication and authorization support in Azure App Service and Azure Functions, and how it can help secure your app.

Contribute to Azure-Samples/remote-mcp-functions-python development by creating an account on GitHub.

How do we create LLMs that can reason? Exploring Test-Time Compute Techniques and DeepSeek-R1.

We have discovered a critical vulnerability in the Model Context Protocol (MCP) that allows for

Understanding multi-agent handoffs Handoffs are a central concept in multi-agent systems. LangGraph swarm is built on them. But, they can be hard to understand. Here, we break-down the swarm handoff mechanism. 📽️: https://t.co/YkSCFeg9A8

Enterprise-grade security, privacy, with features like agents, MCP, prompt templates, and more.

Extend your agent's capabilities with Model Context Protocol servers.

The Model Context Protocol gives users a wide range of services they can connect to from the comfort of their AI client.

Discover how the Model Context Protocol (MCP) simplifies building AI applications by seamlessly integrating Anthropic Claude with Docker Desktop, enhancing developer productivity and workflow efficiency.

Model-Agnostic MCP Library for LLMs

It's MCP week apparently! Yesterday we showed you how to use LlamaCloud as an MCP server, today see how to use LlamaIndex as a client to any MCP…

We introduce THINK-AND-EXECUTE, a framework that performs reasoning with a pseudocode that contains the common logical structure of a given task.

Model Context Protocol Servers

Model Context Protocol (MCP) is actually a concept that is a few months old, but getting so hot...

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

Explore the main components of what makes LLM Agents special.