Semantic Kernel
The latest news from the Semantic Kernel team for developers
Latest posts
Integrating Semantic Kernel Python with Google’s A2A Protocol
Google's Agent-to-Agent (A2A) protocol is designed to enable seamless interoperability among diverse AI agents. Microsoft’s Semantic Kernel (SK), an open-source platform for orchestrating intelligent agent interactions, is now being integrated into the A2A ecosystem. In this blog, we demonstrate how Semantic Kernel agents can easily function as an A2A Server, efficiently routing agent calls to specialized services. You can read more about the A2A protocol in Google's technical documentation. Our Contribution to the A2A Ecosystem Our initial contribution to the A2A repository addresses the current absence of ...
Semantic Kernel adds Model Context Protocol (MCP) support for Python
We are excited to announce that Semantic Kernel (SK) now has first-class support for the Model Context Protocol (MCP) — a standard created by Anthropic to enable models, tools, and agents to share context and capabilities seamlessly. With this release, SK can act as both an MCP host (client) and an MCP server, and you can leverage these capabilities directly in your agents. This unlocks powerful new scenarios for tool interoperability, prompt sharing, and agent orchestration across local and remote boundaries. This requires Semantic Kernel Python version 1.28.1 or higher. What is MCP? MCP is a protocol that ...
Customer Case Study: Announcing the Neon Serverless Postgres Connector for Microsoft Semantic Kernel
Announcing the Neon Serverless Postgres Connector for Microsoft Semantic Kernel We’re excited to introduce the Neon Serverless Postgres Connector for Microsoft Semantic Kernel, enabling developers to seamlessly integrate Neon’s serverless Postgres capabilities with AI-driven vector search and retrieval workflows. By leveraging the pgvector extension in Neon and the existing Postgres Vector Store connector, this integration provides a high-performance, scalable solution for vector embeddings and performing vector similarity search in Postgres. Why Use Neon for Semantic Kernel? Neon is a fully managed Serverless...
Guest Blog: Bridging Business and Technology: Transforming Natural Language Queries into SQL with Semantic Kernel Part 2
Today we'd like to welcome back a team of internal Microsoft employees for part 2 of their guest blog series focused on Bridging Business and Technology: Transforming Natural Language Queries into SQL with Semantic Kernel. We'll turn it over to our authors - Samer El Housseini, Riccardo Chiodaroli, Daniel Labbe and Fabrizio Ruocco to dive in. Introduction In today's data-driven business landscape, access to information is critical for decision-making. However, a persistent challenge has been the technical barrier between business users who need data insights and the complex database systems that house this info...
Guest Blog: Revolutionize Business Automation with AI: A Guide to Microsoft’s Semantic Kernel Process Framework
Revolutionize Business Automation with AI: A Guide to Microsoft’s Semantic Kernel Process Framework Step-by-Step guide on creating your first process with AI Microsoft’s AI Framework, Semantic Kernel, is an easy-to-use C#, Java, and Python-based AI framework that helps you quickly build AI solutions or integrate AI capabilities into your existing app. Semantic Kernel provides various ways to integrate the power of LLM into your application. The two core sub-frameworks that Semantic Kernel offers are Agent-based and Process-based. In my previous blogs I have shared steps to create agents with Semantic Kernel’...
Announcing Hybrid Search with Semantic Kernel for .NET
Today we’re thrilled to announce support for Hybrid search with Semantic Kernel Vector Stores for .NET. What is Hybrid Search? Hybrid search performs two parallel searches on a vector database. The union of the results of these two searches are then returned to callers with a combined rank, based on the rankings from each of the constituent searches. The two searches typically consist of 1. a vector similarity search and 2. a keyword search over the source text of the vector from search 1. Using hybrid search typically results in much better RAG performance than just using regular vector similarity search....
Guest Blog: A Comprehensive Guide to Agentic AI with Semantic Kernel
Today we're excited to welcome Arafat Tehsin, who’s a Microsoft Most Valuable Professional (MVP) for AI. back as a guest author on the Semantic Kernel blog today to cover his work on a Comprehensive Guide to Agentic AI with Semantic Kernel. We'll turn it over to Arafat to dive in further. The world of AI is evolving rapidly and just two weeks back, the Semantic Kernel team rolled out several significant improvements to their Agent Framework for both .NET and Python SDKs. These updates pave the way for more dynamic and flexible applications across various industries. Therefore, I decided to come up with a compr...
Python Vector Store Connectors update: Faiss, Azure SQL Server and Pinecone
Announcing New Vector Stores: Faiss, SQL Server, and Pinecone We are thrilled to announce the availability of three new Vector Stores and Vector Store Record Collections: Faiss, SQL Server, and Pinecone. These new connectors will enable you to store and retrieve vector data efficiently, making it easier to work with your own data and data models. Faiss Faiss is a library for efficient similarity search and clustering of dense vectors. It builds on the built-in InMemoryCollection, by creating Faiss indexes on the side, which are then used for the actual vector search. Setup Install Semantic Kernel with ...
Guest Blog: Semantic Kernel and Copilot Studio Usage Series – Part 1
Today on the Semantic Kernel blog we're excited to welcome a group of guest authors from Microsoft. We'll turn it over to Riccardo Chiodaroli, Samer El Housseini, Daniel Labbe and Fabrizio Ruocco to dive into their use cases with Semantic Kernel and Copilot Studio. In today's fast-paced digital economy, intelligent automation is no longer optional—it's an essential capability for organizations striving to remain competitive and agile. Modern business success depends not merely on adopting advanced technologies, but on seamlessly integrating them into existing operations to enhance productivity, improve custo...