Google’s Agent2Agent protocol finds new home at the Linux Foundation

At the Open Source Summit North America, it was announced that Google donated its Agent2Agent (A2A) protocol to the Linux Foundation.

The A2A protocol offers a standard way for connecting agents to each other. In this way, it complements Anthropic’s Model Context Protocol (MCP), which provides a way to connect agents to different data sources and applications.

“Drawing on Google’s internal expertise in scaling agentic systems, we designed the A2A protocol to address the challenges we identified in deploying large-scale, multi-agent systems for our customers. A2A empowers developers to build agents capable of connecting with any other agent built using the protocol and offers users the flexibility to combine agents from various providers,” Google wrote in a blog post when it first launched A2A in April.

OpenAI adds Deep Research and Webhooks to the API

The addition of Deep Research will enable developers to build research agents that find, analyze, and synthesize data. 

Webhooks were also added, enabling developers to receive notifications for API events like completed responses, fine-tuning jobs, and batch jobs. 

Additionally, the company is dropping the price for web search and adding it into more models. It costs $10 / 1k tool calls in o3, o3-pro, and o4 mini, and $25 / 1k tool calls in GPT-4o and GPT-4.1.  

Anthropic adds ability to host and share Claude apps in its platform

Now, developers will be able to not only interact with Claude, but also use it to build, host, and share their creations, eliminating the need to worry about hosting it themselves.

Users will authenticate with their own Claude account, and their API usage will count against their subscription instead of the app developer being charged.

Qodo launches CLI agent framework

Qodo, maker of an AI coding platform, today announced the release of Qodo Gen CLI, an agent framework that enables developers to create, customize, and deploy their own AI coding agents.

With the framework, creating agents can be done by writing configuration files that add autonomous AI agents throughout the software development life cycle, according to the company’s announcement.

Qodo was built to help developers  add autonomous coding capabilities to their applications without requiring expertise in AI systems, which can lead to solutions that sync up with an organization’s requirements, the company said. With Qodo Gen CLI, developers can define custom agents and what tools they can access, specify actions that trigger the agents, what instructions guide their behavior and ultimately, what their outputs should be.

Warp 2.0 evolves terminal experience into an Agentic Development Environment

Warp is undergoing a significant transformation with its 2.0 launch, shifting from its origins as a terminal emulator with AI integrations into an Agentic Development Environment (ADE).

It consists of four main capabilities: Code, Agents, Terminal, and Drive. Any of those can be initiated from the main interface, which accepts both prompts and terminal commands.

“The products on the market today, from AI IDEs to CLI coding agents, all miss the mark supporting this workflow. They bolt agents onto code editors through chat panels and bury them in CLI apps. What’s needed is a product native to the agentic workflow; one primarily designed for prompting, multi-threading, agent management, and human-agent collaboration across real-world codebases and infrastructure,” Zach Lloyd, the company’s CEO and founder, wrote in a blog post.

Agent Mode for Gemini added to Android Studio

With Agent Mode, a developer can describe a complex goal, then the agent will come up with an execution plan and then complete the tasks. 

Examples of tasks Agent Mode can tackle include building a project and fixing errors, extracting hardcoded strings and migrating them to strings.xml, adding support for dark mode to an app, and implementing a new screen in an app from a screenshot.

Developers will have the ability to review, accept, or reject any of the agent’s proposed changes, or ask it to iterate on their feedback. There is also an auto-approve feature that can be enabled for situations when a developer wants to iterate quickly on ideas.

Vercel Agent launches in limited beta

The Vercel Agent is an AI assistant that analyzes Vercel app performance and security data.

It can summarize anomalies, identify likely root causes, and recommend remediation actions across the entire platform, from managing firewall rules to identifying optimization opportunities. 

Tricentis Agentic Test Automation

This is a new AI agent that can generate test cases automatically, leveraging text-based prompts as well as prior test runs. It also makes use of Tricentis’ Vision AI technology to interpret visual elements across platforms, and integrates with Tricentis Tosca.

Additionally, the company launched a remote MCP server and a beta for its AI workflows capability that enables better communication between agents and humans. 

Read last week’s announcements here.