InfoQ Homepage Agents Content on InfoQ
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Microsoft Releases Azure Functions Support for Model Context Protocol Servers
Microsoft has launched its Model Context Protocol (MCP) for Azure Functions, ensuring secure, standardized workflows for AI agents. With built-in OBO authentication and streamable HTTP transport, it addresses key security concerns. Now supporting multiple languages and self-hosting, MCP empowers developers to deploy with ease while safeguarding sensitive data.
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GitLab 18.8 Marks General Availability of the Duo Agent Platform
GitLab 18.8 brings a number of new features, including GitLab Duo Planner Agent, GitLab Duo Security Analyst Agent, auto-dismiss irrelevant vulnerabilities, and more. With this release, the GitLab Duo Agent Platform, enabling organizations to orchestrate AI agents, reaches general availability.
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Docker’s Cagent Brings Deterministic Testing to AI Agents
Docker is positioning its Cagent runtime as a way to bring deterministic testing back to AI agents, addressing a growing problem for teams building production agentic systems.
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Android Studio Otter Boosts Agent Workflows and Adds LLM Flexibility
The latest Android Studio Otter feature drop introduces several new features that make it easier for developers to integrate AI-powered tools in their workflows, including the ability to set which LLM to use, enhanced agent mode through device interaction, support for natural language testing, and more.
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AI-Powered Code Editor Cursor Introduces Dynamic Context Discovery to Improve Token-Efficiency
Cursor introduced a new approach to minimize the context size of requests sent to large language models. Called dynamic context discovery, this method moves away from including large amounts of static context upfront, allowing the agent to dynamically retrieve only the information it needs. This reduces token usage and limits the inclusion of potentially confusing or irrelevant details.
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Vercel Open-Sources Bash Tool for Context Retrieval Using Local Filesystems
Vercel has open-sourced bash-tool that provides a Bash execution engine for AI agents, enabling them to run filesystem-based commands to retrieve context for model prompts.
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LangGrant Unveils LEDGE MCP Server to Enable Agentic AI on Enterprise Databases
LangGrant has launched the LEDGE MCP Server, a new enterprise platform designed to let large language models reason across complex database environments without directly accessing or exposing underlying data.
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DeepSeek-V3.2 Outperforms GPT-5 on Reasoning Tasks
DeepSeek released DeepSeek-V3.2, a family of open-source reasoning and agentic AI models. The high compute version, DeepSeek-V3.2-Speciale, performs better than GPT-5 and comparably to Gemini-3.0-Pro on several reasoning benchmarks.
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Intel DeepMath Introduces a Smart Architecture to Make LLMs Better at Math
Intel has announced DeepMath, a lightweight agent built on Qwen3-Thinking that specializes in solving mathematical problems. To address common limitations of LLMs in math reasoning, DeepMath generates small Python scripts that support and enhance its problem-solving process.
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Google’s Eight Essential Multi-Agent Design Patterns
Google recently published a guide outlining eight essential design patterns for multi-agent systems, ranging from sequential pipelines to human-in-the-loop architecture. The guide provides concrete explanations of each pattern along with sample code for Google's Agent Development Kit.
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Open-Source Agent Sandbox Enables Secure Deployment of AI Agents on Kubernetes
The Agent Sandbox is an open-source Kubernetes controller that provides a declarative API for managing a single, stateful pod with stable identity and persistent storage. It is particularly well suited for creating isolated environments to execute untrusted, LLM-generated code, as well as for running other stateful workloads.
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Microsoft Foundry Agent Service Simplifies State Management with Long-Term Memory Preview
Microsoft has launched a public preview of a managed long-term memory store for its Foundry Agent Service. The service automates the extraction, consolidation, and retrieval of user context, providing a native "state layer" that prevents intelligence decay in long-running interactions with AI agents.
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OpenAI and Anthropic Donate AGENTS.md and Model Context Protocol to New Agentic AI Foundation
OpenAI and Anthropic have donated their AGENTS.md and Model Context Protocol projects to the Agentic AI Foundation (AAIF), a new directed fund under the Linux Foundation. Block contributed their agent framework, goose, as another founding project, and several other tech companies have joined as Platinum members.
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Toad: a Unified CLI Tool for All Your LLMs That Promises Improved UX from Existing Ones
During his sabbatical, Will McGugan, maker of Rich and Textual, frameworks for making Textual User Interfaces (TUI), put his UI skills to work to build Toad. The newly publicly released tool aims to provide a unified, "beautiful" GUI for multiple coding agents in your terminal, accessible via the same tool via the Agent Communication Protocol (ACP).
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IBM Research Introduces CUGA, an Open-Source Configurable Agent Framework on Hugging Face
IBM Research has released CUGA (Configurable Generalist Agent) on Hugging Face Spaces, making its enterprise-oriented agent framework easier to evaluate with open models and real workflows. The move positions CUGA as a practical alternative to brittle, tightly coupled agent frameworks that often struggle with tool misuse, long-horizon reasoning, and recovery from failure.