Recently, leading AI companies announced support for remote MCP, allowing an MCP client to connect to a remote MCP server via Streamable HTTP, which still supports Server-Sent Events (SSE). The Streamable Data Input/Output (SDIO) protocol remains essential for local integrations and remote services, which are accessible only through conventional APIs. In my opinion, the excitement surrounding new model releases has lost its significance. AI model developers seem to primarily focus on optimizing their models for AI benchmarks. However, the genuine innovations occur in the technologies surrounding AI models—most notably in AI agents and the supporting infrastructure in which remote MCP servers will play an important role.

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The VS Code May 2025 update (version 1.101), released a few days ago, introduces a range of new features primarily focused on GitHub Copilot. My favorite addition is the custom chat mode, which lets you create a personalized mode alongside the built-in options: Ask, Edit, and Agent. In this post, I'll also explore the new chat tool sets and the undoing edits feature. While the Simple Browser feature was included in the previous release, it deserves discussion. Furthermore, I will briefly summarize the MCP enhancements.

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The MCP catalog in Docker Desktop has been available for a couple of weeks now. However, MCP support only works properly in the just-released Docker Desktop 4.42. The Docker Desktop MCP server catalog significantly simplifies installing MCP servers for any MCP client. I tested it with Gordon (Docker Desktop chatbot), Anthropic Claude Desktop, and VS Code GitHub Copilot on macOS, but the process should be identical on Windows.

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Warp, the top terminal app with AI support, has introduced new features in its GA release, including MCP support and Refine for AI responses. The Preview release now allows image uploads and the saving of reusable AI prompts. I also found a few new features that weren’t mentioned in the Launch Log 3 post.

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Vous voulez booster votre productivité avec l’IA sans passer trois heures à configurer des serveurs et à lire de la doc technique barbante ? Bref, vous avez envie d’utiliser un super Model Context Protocol pour connecter Claude à vos outils préférés, mais là, c’est le drame !! Vous devez télécharger des repos GitHub, décortiquer la documentation, configurer des serveurs, gérer les dépendances… En somme, vous passez plus de temps à installer qu’à vraiment bosser. Et ça, c’est carrément frustrant quand on veut juste tester un truc cool rapidos !

The Gmail MCP server covered in this post lets you access Gmail from any AI client that supports MCP. I found the MCP server more capable than Google's integration with Gemini in Gmail. The AI-powered search feature proved to be helpful, but the MCP server also offers several other valuable commands. In this post, I used Claude Desktop. However, once you install the MCP server and set up the Gmail API, you can access Gmail through MCP from any compatible AI application by copying the MCP JSON. I expect that the ChatGPT app and even Windows 11 will add MCP support very soon.

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OpenAI recently introduced the Agents SDK, a Python-based framework that enables developers and DevOps engineers to build AI agents. The example in this post showcases a script that uses the OpenAI Agents SDK to connect an AI agent to Anthropic’s filesystem MCP server. This integration enables the AI agent to analyze the contents of a monitoring log.

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OpenAI's Sam Altman envisions a future where countless AI agents operate autonomously across the internet, managing tasks on behalf of users and interacting with each other to perform complex operations without human intervention. Realizing this vision necessitates a new internet protocol that supports the sophisticated communication required for AI systems. Google’s new Agent2Agent (A2A) Protocol addresses this need by providing an open standard that enables autonomous AI agents to communicate across diverse systems. This post delves into the necessity of A2A, its current supporters, distinctions from Anthropic’s Model Context Protocol (MCP), the types of data it handles, and offers a straightforward example to illustrate its application.

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In a remarkably short period, MCP has established itself as the standard for secure and efficient connections between AI models and external data sources and tools. Microsoft has integrated MCP into VS Code, Windows will get it, OpenAI plans to implement it for ChatGPT, and the top terminal application, Warp, has introduced MCP support in its Preview version. I installed the official Perplexity MCP server for my test and incorporated it into Warp.

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Perplexity is an AI search engine that answers questions by combining real-time web results with conversational, natural language responses. Installing Perplexity's official MCP server on your Mac or Windows PC allows querying Perplexity from any AI model in VS Code GitHub Copilot. Enabling your AI to search the web for the latest updates is a must-have feature for scripting or working in the terminal.

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I compared six frontier AI models—DeepSeek V3, Anthropic Claude Sonnet 3.7, Google Gemini 2.5 Pro, Meta Llama 4 Maverick, OpenAI GPT 4o (GPT 4.1), and Mistral Large 2—in terms of their capabilities in interacting with MCP servers. Surprisingly, the performance in terms of accuracy, token usage, and API costs are quite different..

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Si vous faites partie des 97% de dev à grosses lunettes qui utilisent des assistants IA comme GitHub Copilot, Windsurf ou Cursor, ce que vous allez lire va probablement flinguer votre journée…

Et oui parce que si vous pensiez que votre assistant IA préféré était votre meilleur atout pour coder, sachez que des chercheurs en sécurité viennent de découvrir qu’en réalité, tous ces outils pourraient se comporter en cheval de Troie placé directement dans votre IDE. Et le plus flippant c’est que vous ne verriez absolument rien venir, même en scrutant le code ligne par ligne.

LLMs' knowledge cutoff date is a significant issue, often resulting in outdated responses. Some frontier models can browse the web, but they frequently skip this ability because they think they can handle things on their own. Bringing in an MCP server that can search the web helps the AI stay updated and assist it when struggling with a problem. Tavily is a research search engine designed to summarize online content for AI models. In this post, I will guide you through installing the Tavily MCP server on Windows. Installing on a Mac follows a similar process.

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Playwright is an open-source framework by Microsoft for automating web browsers to perform end-to-end testing, scraping, and UI interactions across Chromium, Firefox, and WebKit. The Playwright MCP server lets AI agents like GitHub Copilot control a web browser using Playwright’s automation capabilities. Microsoft introduced support for MCP in Visual Studio Code 1.99 (March 2025), enabling tools like the Copilot Agent to connect with external services. In this post, I explain how to install the Microsoft Playwright MCP server in VS Code for the GitHub Copilot Agent.

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In March 2025, the release of VS Code version 1.99 introduced support for Anthropic's Model Context Protocol (MCP) in GitHub Copilot's Agent Mode. This open standard is now backed by leading AI companies such as Google, Amazon, Microsoft, and OpenAI. MCP provides a standardized framework that allows AI models to interact with external tools and data sources. In this post, I will guide you on how to install, start, stop, activate, and deactivate MCP servers. You will also learn to configure settings in mcp.json and settings.json, as well as import MCP servers from Claude Desktop, Cline, and Roo Code.

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The AI tools for the Command Line Interface (CLI) we discussed on 4sysops connect the terminal to AI models. For example, the Warp terminal includes AI tools designed to help admins working on a CLI. The Windows CLI MCP Server does the opposite. If you missed it, the Model Context Protocol (MCP) is a new open standard for AI agent communication with software services created by Anthropic and backed by OpenAI, Amazon, and Microsoft. With MCP, your primary interface is the chatbot, and for the Windows CLI MCP Server, shell access is an additional tool the AI can utilize. The Windows CLI MCP Server supports PowerShell, CMD, Git Bash shells, and remote SSH.

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Zapier is a cloud-based automation platform that lets users connect and automate workflows between thousands of web services without coding. Recently, Zapier announced support for Anthropic's MCP standard. MCP is an open protocol that allows AI models to interact with external tools, data sources, and services, and it's now also supported by OpenAI, Microsoft, and Amazon. In this post, I share my experiences with Zapier's MCP server.

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