MCP App StoreThe latest from the AI and MCP ecosystem, curated daily.
Sources
OpenAI has updated the Agents SDK to include native sandbox execution and a model-native harness. These enhancements enable developers to build more secure, long-running agents capable of complex operations across files and tools.
HCompany introduces HoloTab, an AI-powered browser companion designed to enhance web navigation and interaction. It aims to streamline how users interact with web content through integrated AI assistance.
Cursor introduces interactive canvases, allowing agents to create and present visual representations of information for better user interaction.
Detailed look at session management in Claude Code, including context compacting and the use of subagents to keep parent context clean within 1M token limits.
A University of Chicago study shows a 44% increase in AI usage as model capabilities improve, specifically driving growth in complex, cross-system work. It highlights how frontier models are shifting the boundary of what's possible in professional workflows.
Cursor demonstrated a multi-agent system that autonomously optimized 235 CUDA kernels for NVIDIA Blackwell 200 GPUs. The approach achieved a 38% geomean speedup over baselines in just three weeks, showcasing the power of agentic optimization for low-level performance.
Claude Code now supports routines, allowing developers to define repeatable AI workflows for tasks like backlog grooming and PR reviews. This brings a level of automation to the developer inner loop.
Anthropic explores the architectural decoupling of agent reasoning (the brain) from execution (the hands) to enable better scaling and reliability in managed agents. This approach allows for more robust control and observability when deploying agents at scale.
Anthropic has redesigned the Claude Code desktop app to support running multiple tasks concurrently. This update focuses on improving productivity for developers managing complex coding workflows.
OpenAI introduces GPT-5.4-Cyber to vetted cybersecurity defenders through an expanded Trusted Access program. The move aims to strengthen AI-driven cyber defense while maintaining strict safeguards.
Cloudflare integrates GPT-5.4 and Codex into Agent Cloud, allowing enterprises to scale agentic workflows with improved security and speed. This partnership focuses on deploying real-world AI agents at the edge.
LangChain explores the critical relationship between agent harnesses and memory, arguing that the choice of harness dictates how an agent retains and retrieves context. The post emphasizes the need for control over memory layers to avoid the limitations of proprietary, closed-API harnesses.
OpenAI has responded to a supply chain attack involving Axios by rotating macOS code signing certificates and updating apps. No user data was compromised in the incident.
A deep dive into the design philosophy behind Claude Code's tools. It discusses the concept of "progressive disclosure" and how to build agent tools that maximize effectiveness by aligning with how LLMs perceive data.
Anthropic outlines five distinct patterns for coordinating multiple agents, detailing the trade-offs of each. This guide provides a framework for developers to decide when to evolve their agent architecture from simple loops to complex coordinated systems.
A guide on shoring up security defenses against AI-driven offensive tactics. It provides actionable recommendations for security teams to adapt their practices to a landscape where attackers use LLMs to accelerate offense.
LangChain announced Deep Agents Deploy in beta: a production-ready, model-agnostic agent deployment harness that streamlines shipping agent-backed applications. This lowers the operational friction for teams who want to run agentic workflows across different model providers and focuses on developer ergonomics and scalability.
LangChain outlines how human-in-the-loop feedback and institutional knowledge can be integrated into agent training and evaluation to improve reliability and alignment. The post is practical for teams building agent workflows that need to capture tacit knowledge and operational judgment without sacrificing automation.
Hugging Face released Gemma, a new family of open models focused on efficient multimodal and developer-friendly APIs. This brings more open alternatives for developers building agentic and embedding-driven systems, lowering barriers for experimentation and deployment.
Hugging Face introduced multimodal embedding and reranker models built on Sentence Transformers, improving retrieval and ranking for mixed text/image workloads. This matters for developers building multimodal agents and search systems because it simplifies creating embeddings and rerankers that handle images alongside text.