Stablecoins are cryptocurrency tokens intended to hold their value at a certain price point, usually $1, and are backed by another asset. The Genius Act, signed by President Donald Trump in July, is expected to boost the popularity of stablecoin currencies. Tether is the largest stablecoin issuer, followed by Circle Internet Group (CRCL). More payments companies are jumping on the stablecoin bandwagon, including PayPal Holdings (PYPL). Will AI Agents Take Off In E-Commerce? TRENDING: Are AI Stocks Driving A ...

由大语言模型（LLMs）驱动的人工智能代理（AI Agents）有潜力彻底改变我们与信息的互动方式并让复杂任务自动化。然而，要真正发挥作用，它们必 须有效地利用外部上下文和数据源，使用专业工具，并生成及执行代码。虽然 AI Agent 能够使用工具，但将这些外部组件集成进来，并使 AI Agent 与这 些工具协同工作一直是重大的难关，通常需要定制的、与框架绑定的解决方案。这导致了生态系统的碎片化，引入重复劳动并带来了难以维护和扩展的系 统。 于是，模型上下文协议（Model Context Protocol，MCP）应运而生。它由 Anthropic 于 2024 年底推出，正迅速成为"AI 的 USB-C"——一个旨在无缝连 接 AI Agent 与它们所需的工具和数据的开放、通用标准。本文深入探讨了 MCP 的含义，它如何增强 Agent 开发，以及它在领先的开源框架中被采用的 情况。我们还讨论了 MCP 解锁的关键能力和其在现实世界中的应用。对于从业者、工程师和研究人员来说，理解 MCP 对于构建下一代强大、上下文感 知和模块化的 AI 系统来说是愈加重要的事情。 理解模型上下文协议 作者 | San ...

NEW YORK, July 31, 2025 /PRNewswire/ -- Globant (NYSE: GLOB), a digitally native company focused on reinventing businesses through innovative technology solutions, today announced a major upgrade to its proprietary AI platform, Globant Enterprise AI (GEAI), which now supports both Model Context Protocol (MCP) and Agent2Agent (A2A) Protocol. This update increases the platform's interoperability, enabling the seamless integration of agents and tools defined in other frameworks and helping Globant continue to ...

Core Insights - BigCommerce and Feedonomics have announced a strengthened partnership with Google Cloud to enhance merchant performance through advanced AI tools [1][2][3] Group 1: Partnership and Innovations - The collaboration aims to improve product discoverability and increase conversion rates for BigCommerce merchants within the Google Cloud ecosystem [2] - Key innovations include Feedonomics Surface for optimizing product data delivery to Google Merchant Center, enhancing visibility across sales channels [6] - AI-powered data enrichment features will allow merchants to automatically enhance product catalogs, improving search performance and conversion rates [6] Group 2: Benefits for Merchants - The partnership provides merchants with enterprise-grade scalability, security, and performance necessary for success in the evolving agentic commerce landscape [3] - Advanced developer tools, combining BigCommerce's Model Context Protocol with Google's Agent Development Kit, will enable the creation of intelligent, commerce-aware merchant agents [6] Group 3: Company Backgrounds - BigCommerce is a leading open SaaS ecommerce platform serving B2C and B2B businesses globally, with a diverse customer base across 150 countries [4] - Feedonomics is a prominent data management platform that supports omnichannel growth for top brands and retailers, with numerous integrations and partnerships [5]

Core Insights - MongoDB is experiencing growth driven by the increasing demand for AI-powered applications, reporting revenues of $549 million in Q1 fiscal 2026, a 22% year-over-year increase [1] - The company's cloud platform, Atlas, contributed 72% of total revenues, with a 26% year-over-year growth [1] - MongoDB's integrated architecture is expected to capture long-term revenue growth as more developers create custom AI applications [1] Group 1: AI Capabilities and Developments - MongoDB's document model is effective for managing unstructured data, essential for AI applications, further enhanced by the acquisition of Voyage AI, which improved embedding accuracy and reduced storage costs [2] - The introduction of Anthropic's Model Context Protocol (MCP) across all databases allows AI agents to access tools and data, facilitating natural language queries and improving developer productivity [3] - Advanced rerankers and domain-optimized embedding models are being utilized to reduce AI hallucinations and enhance output accuracy [4] Group 2: Competitive Landscape - MongoDB faces increasing competition from Snowflake and Elastic, both enhancing their AI capabilities in the cloud database market [5] - Snowflake has introduced native support for vector search and retrieval-augmented generation (RAG) workloads, while Voyage AI's models will remain available to Snowflake users [5] - Elastic has expanded its AI features with the Elasticsearch Relevance Engine, supporting native vector search and integration with large language models (LLMs) [6] Group 3: Financial Performance and Valuation - MongoDB shares have declined by 11.8% year-to-date, underperforming the Zacks Internet – Software industry growth of 15.8% and the Zacks Computer and Technology sector return of 7.7% [7] - The stock is currently trading at a forward 12-month Price/Sales ratio of 7.03X, compared to the industry's 5.79X, indicating a lower valuation score [11] - The Zacks Consensus Estimate for Q2 fiscal 2026 earnings is 64 cents per share, reflecting an 8.57% year-over-year decline [15]

Heroku Managed Inference and Agents Platform Overview - Heroku Managed Inference and Agents platform enables developers to build agentic applications that can reason, make decisions, and trigger actions [1] - The platform allows for provisioning and deploying LLMs, running untrusted code securely in multiple languages, and extending agents with the Model Context Protocol (MCP) [1] Key Capabilities - Heroku Managed Inference and Agents facilitates the deployment and management of LLMs [1] - The platform supports secure execution of untrusted code in Python, Nodejs, Go, and Ruby [1] - Model Context Protocol (MCP) can be used to extend agent capabilities [1] Target Applications - The platform is suitable for building internal tools, developer assistants, or customer-facing AI features [1]

Workshop Overview - The workshop focuses on building AI agents using Amazon's agent technologies [1] - Participants will gain hands-on experience in building sophisticated AI agents [1] - The workshop is 2-hour long [1] Technologies Highlighted - Amazon Nova Act is used for reliable web navigation [1] - Model Context Protocol (MCP) connects agents to external data sources and APIs [1] - Amazon Bedrock Agents orchestrates complex workflows [1] Skills Acquired - Participants will learn to build agents that can navigate the web like humans [1] - Participants will learn to perform complex multi-step tasks [1] - Participants will learn to leverage specialized tools through natural language commands [1]

Core Insights - The article discusses the competitive landscape of AI startups and emphasizes the need for entrepreneurs to leverage AI capabilities effectively in order to survive against larger companies [1][3]. Group 1: AI Programming Revolution - Anthropic's current codebase is 90% generated by AI, a significant increase from zero just a few years ago [4]. - Over 70% of code submissions are now generated by Claude Code, exceeding expectations [4]. - The development process has become more efficient, allowing team members to contribute without needing to master specific programming languages [5]. Group 2: Transformation in Product Development - Traditional product development processes have been disrupted, with product managers now able to create prototypes directly using AI tools [6]. - New bottlenecks have emerged in decision-making and code deployment due to the rapid generation of code [7]. - Code review processes have evolved, with AI now assisting in code reviews to manage the increased volume of submissions [7]. Group 3: Advice for AI Entrepreneurs - Entrepreneurs should focus on vertical industries where they can leverage specialized knowledge [8]. - Building differentiated sales capabilities is crucial, requiring a deep understanding of internal decision-making processes within target companies [9]. - There are opportunities for interface innovation beyond traditional chat interfaces, which can redefine user interaction with AI [10]. Group 4: Product and Model Team Integration - Anthropic has found that breakthroughs in product development come from integrating product teams directly with research teams [12]. - This integration allows for a more organic fusion of model capabilities and user needs, enhancing product development [13]. Group 5: Competitive Landscape and Differentiation Strategy - Anthropic does not aim to replicate the success of ChatGPT but instead focuses on building a strong community of creators [14]. - The company seeks to position itself as the preferred tool for those looking to create value with AI [15]. Group 6: Model Context Protocol (MCP) - MCP is introduced as a crucial innovation to enhance AI's contextual understanding and memory capabilities [16]. - The protocol aims to standardize integrations, making it easier for developers to create solutions that can be used across different AI platforms [17]. Group 7: Utilizing Anthropic's API - Companies that challenge the limits of AI models tend to benefit the most from new releases [18]. - Establishing a robust evaluation system for new model releases is essential for assessing improvements [18]. Group 8: Future Outlook - Predictions about AI model capabilities are becoming more reliable, with significant progress already observed [20]. - The focus is on shaping a future where AI can effectively assist in various tasks, enhancing productivity and creativity [21]. Group 9: Education in the AI Era - The article emphasizes the importance of fostering independent thinking and problem-solving skills in children, rather than over-relying on AI [28][29].