News from the AI & ML world
DeeperML - #interoperability
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@the-decoder.com
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THE DECODER
, AI News | VentureBeat
Microsoft is making a significant push towards AI interoperability by adding support for the Agent2Agent (A2A) protocol to its Azure AI Foundry and Copilot Studio. This move aims to break down the walled garden approach to AI development, allowing AI agents built on different platforms to communicate and collaborate seamlessly. Satya Nadella, Microsoft's CEO, has publicly endorsed both Google DeepMind's A2A and Anthropic's Model Context Protocol (MCP), signaling a major industry shift toward open standards. Nadella emphasized the importance of protocols like A2A and MCP for enabling an agentic web, where AI systems can interoperate by design.
This commitment to interoperability will allow customers to build agentic systems that can work together regardless of the platform they are built on. Microsoft's support for A2A will enable Copilot Studio agents to call on external agents, even those outside the Microsoft ecosystem or built with tools like LangChain or Semantic Kernel. According to Microsoft, Copilot Studio is already used by over 230,000 organizations, including 90 percent of the Fortune 500, suggesting a potentially wide adoption of A2A-enabled agentic collaboration. A public preview of A2A in Azure Foundry and Copilot Studio is expected to launch soon. OpenAI is also contributing to the advancement of AI interoperability through its Agents SDK, introduced in March. This SDK provides a framework for building multi-agent workflows, allowing developers to define agent behavior, connect to external tools, and manage the action flow. The Agents SDK also supports the Model Context Protocol (MCP), enabling agents to discover and call functions from any compatible server. By supporting open standards like A2A and MCP, both Microsoft and OpenAI are fostering a future where AI agents can work together to automate daily workflows and collaborate across platforms, promoting innovation and avoiding vendor lock-in. Recommended read:
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Ken Yeung@Ken Yeung
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pub.towardsai.net
HubSpot has launched a public beta of its Model Context Protocol (MCP) server, empowering developers to integrate AI applications with customer relationship management (CRM) data. This offering, provided as an NPM package, is specifically designed for developers, technical teams, and businesses seeking to create custom applications or integrations using large language models (LLMs). The MCP server allows AI applications like Claude and Cursor to directly access HubSpot data, facilitating tasks such as retrieving, creating, or modifying HubSpot objects, listing properties, and generating tasks and notes using natural language. This allows users to streamline development and gain insights, demonstrated by examples such as summarizing deals or updating customer information.
The Model Context Protocol standardizes the way AI models connect to applications through a consistent interface. HubSpot describes MCP as an abstraction layer over traditional APIs, enabling AI agents to access application functionality without needing to understand specific API protocols. This mirrors the function of API feeds from companies like Google, Facebook, and Salesforce, providing a standardized connection point in the AI era. By opening its MCP server, HubSpot aims to equip small and medium-sized businesses (SMBs) with the tools to leverage AI in a manner previously accessible only to larger enterprises. Microsoft CEO Satya Nadella has also endorsed the Model Context Protocol, signaling a shift towards open standards for AI interoperability. Nadella’s support, along with his endorsement of Google DeepMind's Agent2Agent (A2A) protocol, is expected to accelerate AI-based collaboration and the development of agentic AI applications. He announced upcoming support for A2A and MCP in Copilot Studio and Foundry, emphasizing that open protocols are key to enabling the agentic web. This move aligns with Nadella's history of championing open, interoperable AI architectures, promoting the idea that open standards, rather than proprietary silos, drive the adoption of new AI technologies. Recommended read:
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Chris McKay@Maginative
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Microsoft is formally partnering with Google on the Agent2Agent (A2A) protocol, signaling a major step towards interoperability in AI systems. This move will enable AI agents to communicate and collaborate across different platforms and organizational boundaries, a previously significant limitation of current AI technology. Microsoft is integrating the A2A protocol into its Azure AI Foundry and Copilot Studio, allowing enterprise customers to build multiagent workflows that span partner tools and production infrastructure. This partnership reflects the industry’s recognition that achieving seamless AI collaboration requires shared standards and open protocols.
The endorsement of Google DeepMind's A2A protocol and Anthropic’s Model Context Protocol (MCP) by Microsoft CEO Satya Nadella is expected to accelerate the development and adoption of agentic AI. Nadella's support is seen as a catalyst for further collaboration within the AI community, potentially leading to the creation of new agentic-based applications and platforms. He highlighted the importance of open protocols like A2A and MCP for enabling an agentic web, emphasizing that these standards allow customers to build agentic systems that interoperate by design. This commitment to open architectures aligns with Nadella’s long-standing belief that open standards are crucial for driving the adoption of new AI technologies. Microsoft is joining over 50 technology partners, including Salesforce, Oracle, and SAP, in supporting the A2A standard created by Google. The company is also actively contributing to the A2A working group on GitHub, a Microsoft subsidiary, to further develop the specification and tooling. The A2A protocol allows AI agents to securely exchange goals, manage state, invoke actions, and return results, facilitating complex workflows across multiple specialized agents. Microsoft’s commitment to A2A underscores the shift towards an "open garden" approach, where AI systems can effectively work together regardless of their origin, marking a foundational shift in how software is built and decisions are made. Recommended read:
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@the-decoder.com
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Microsoft is embracing interoperability in the AI agent space by integrating Google's open Agent2Agent (A2A) protocol into its Azure AI Foundry and Copilot Studio platforms. This move aims to enable AI agents to seamlessly collaborate across diverse platforms and ecosystems. A2A defines how a client agent formulates tasks and a remote agent executes them, supporting both synchronous and asynchronous task handling with status updates exchanged via the protocol. By adopting A2A, Microsoft is fostering a future where AI agents can work together regardless of the underlying framework or vendor, promoting cross-platform compatibility and enhancing AI application development efficiency.
Microsoft's A2A support will allow Copilot Studio agents to interact with external agents, including those built using tools like LangChain or Semantic Kernel, even those outside the Microsoft ecosystem. This means agents can delegate tasks, share data, and act together to automate daily workflows. Microsoft promises full integration with existing security and governance systems, including Microsoft Entra and audit logging. Over 230,000 organizations already use Copilot Studio, including 90 percent of the Fortune 500. Developers can access sample applications, such as automated meeting scheduling between two agents. Google introduced the A2A protocol in April with more than 50 technology partners and is designed to let agents work together using standardized interfaces like HTTP and JSON-RPC. Microsoft is contributing to the specification work on GitHub and plans to help drive further development. A public preview of A2A in Azure Foundry and Copilot Studio is set to launch soon. Microsoft sees protocols like A2A as the foundation for a new kind of software architecture, where connected agents automate daily workflows and collaborate across platforms, without vendor lock-in, but with auditability and control. Recommended read:
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Adit Sheth@Towards AI
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The Model Context Protocol (MCP) is rapidly gaining traction as a crucial standard for enabling AI agents to effectively interact with real-world tools and applications. Developed by Anthropic and supported by major players like OpenAI, Microsoft, and Dremio, MCP aims to standardize how agents interact with various systems and data sources, acting as a "USB-C for AI applications." This allows AI agents to work more independently, learn, adapt, and plan autonomously, expanding their capabilities beyond traditional AI tasks by facilitating communication with external tools and services.
MCP addresses the problem of context fragmentation in AI development. Currently, AI agents often need custom code for each tool they interact with, leading to complexity and scalability issues. MCP provides a single interface for agents to connect to, translating requests and routing them to the appropriate tool behind the scenes. This simplifies integration and creates a cleaner, more scalable setup. The protocol enables agents to discover available capabilities, understand how to use them, and invoke them dynamically in real-time, streamlining the process of accessing and utilizing external resources. Examples of MCP's versatility include enabling AI agents to exchange multimedia messages on WhatsApp, conduct deep web searches, generate music from prompts, and design user interfaces with Figma. For instance, Dremio utilizes MCP to allow agents to access and interact with structured data through SQL, while also translating natural language queries into executable SQL. Auth0 integrates with MCP to provide secure AI agents with identity and access controls. The LangChain MCP adapter further simplifies development by allowing developers to build MCP agents using Composio's managed MCP server, demonstrating the growing ecosystem and its potential to transform AI application development. Recommended read:
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Ken Yeung@Ken Yeung
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Google has launched Agent2Agent (A2A), an open interoperability protocol designed to facilitate seamless collaboration between AI agents across diverse frameworks and vendors. This initiative, spearheaded by Google Cloud, addresses the challenge of siloed AI systems by standardizing communication, ultimately automating complex workflows and boosting enterprise productivity. The A2A protocol has garnered support from over 50 technology partners, including industry giants like Salesforce, SAP, ServiceNow, and MongoDB, signaling a broad industry interest in fostering a more cohesive AI ecosystem. A2A aims to provide a universal framework, allowing AI agents to securely exchange information, coordinate actions, and integrate across various enterprise platforms, regardless of their underlying framework or vendor.
The A2A protocol functions on core principles of capability discovery, task management, collaboration, and user experience negotiation. Agents can advertise their capabilities using JSON-formatted "Agent Cards," enabling client agents to identify the most suitable remote agent for a specific task. It facilitates lifecycle management for tasks, ensuring real-time synchronization. Built on established standards like HTTP and JSON, A2A ensures compatibility with existing systems while prioritizing security. Google has released A2A as open source, encouraging community contributions to enhance its functionality. Enterprises are beginning to use multi-agent systems, with multiple AI agents working together, even when built on different frameworks or providers. By enabling interoperability between specialized agents, A2A addresses a critical barrier to scaling agentic AI solutions, unifying workflows and reducing integration costs. Vertex AI is enhancing its services to help move towards a multi-agent ecosystem, including Agent Development Kit, Agent2Agent Protocol, Agent Garden, and Agent Engine. The protocol aims to foster innovation in AI while ensuring trustworthiness and scalability as enterprises adopt AI agents for various tasks. Recommended read:
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@www.analyticsvidhya.com
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Google Cloud Next '25 saw a major push into agentic AI with the unveiling of several key technologies and initiatives aimed at fostering the development and interoperability of AI agents. Google announced the Agent Development Kit (ADK), an open-source framework designed to simplify the creation and management of AI agents. The ADK, written in Python, allows developers to build both simple and complex multi-agent systems. Complementing the ADK is Agent Garden, a collection of pre-built agent patterns and components to accelerate development. Additionally, Google introduced Agent Engine, a fully managed runtime in Vertex AI, enabling secure and reliable deployment of custom agents at a global scale.
Google is also addressing the challenge of AI agent interoperability with the introduction of the Agent2Agent (A2A) protocol. A2A is an open standard intended to provide a common language for AI agents to communicate, regardless of the frameworks or vendors used to build them. This protocol allows agents to collaborate and share information securely, streamlining workflows and reducing integration costs. The A2A initiative has garnered support from over 50 industry leaders, including Atlassian, Box, Cohere, Intuit, and Salesforce, signaling a collaborative effort to advance multi-agent systems. These advancements are integrated within Vertex AI, Google's comprehensive platform for managing models, data, and agents. Enhancements to Vertex AI include supporting Model Context Protocol (MCP) to ensure secure data connections for agents. In addition to software advancements, Google unveiled its seventh-generation Tensor Processing Unit (TPU), named Ironwood, designed to optimize AI inferencing. Ironwood offers significantly increased compute capacity and high-bandwidth memory, further empowering AI applications within the Google Cloud ecosystem. Recommended read:
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