MCP App StoreLe meilleur de l'écosystème IA et MCP, sélectionné chaque jour.
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OpenAI introduces custom code review rules for Codex, allowing developers to define specific conventions and patterns for the AI to enforce. This helps maintain codebase consistency and catch domain-specific bugs during automated reviews.
OpenAI details how to connect private MCP servers to their products while maintaining secure network boundaries. This enables streaming and authentication for internal tools without exposing them to the public internet.
OpenAI introduces Codex Remote, allowing developers to use their mobile devices as a control center for steering and organizing engineering workflows. This increases accessibility for managing remote agentic work on the go.
Perplexity shares how they built and scaled their voice search agent using OpenAI's Realtime API — covering architecture decisions, latency optimisation, and lessons from shipping to millions of users. A detailed case study of production voice AI at real scale, with practical takeaways for teams building speech-to-speech agents.
OpenAI shares practical prompting and structuring techniques for steering GPT-5.4 toward polished, production-ready frontend designs — covering layout generation, component consistency, and how to give the model enough design context to produce genuinely usable UI. Useful for teams using AI to accelerate frontend work.
OpenAI marks one year of the Responses API with five developer stories showing how teams have used it to build production agentic products — from automated research tools to customer-facing agents. A good snapshot of what the Responses API enables in practice, beyond the launch-day demos.
OpenAI's team shares how they use agent skills and GitHub Actions to automate maintenance workflows across the OpenAI Agents SDK repos — handling issue triage, PR reviews, changelog updates, and documentation. A practical example of skills used for developer tooling maintenance rather than user-facing products.
OpenAI demonstrates a bidirectional Codex + Figma workflow: generate a running UI with Codex, bring it into Figma for design refinement, then sync changes back to Codex for implementation. This closes the design-to-code loop in a way that keeps both designers and developers in their preferred tools. An interesting workflow for teams bridging design and AI-assisted development.
OpenAI details how to use Codex for long-horizon tasks — multi-step jobs that run autonomously without constant user input. The post covers structuring tasks for reliable execution, using hosted shell and background mode, and managing state across extended agent runs. Essential patterns for anyone building production Codex workflows.
OpenAI shares practical patterns for building agents that do real sustained work — combining agent skills, hosted shell execution, and server-side context compaction in the Responses API. Covers how to keep long-running agents from hitting context limits and how compaction lets them work across sessions. Useful for anyone building beyond simple single-turn agents.
OpenAI distills 15 hard-won lessons from building ChatGPT Apps — covering UX patterns, capability design, handling ambiguity, and how they packaged the learnings into a Codex Skill to bootstrap new apps 10x faster. Practical and opinionated guide for anyone building on the ChatGPT Apps SDK.
OpenAI explains how to build a systematic eval harness for agent skills — turning skills into testable, scoreable artefacts you can improve over time. The post covers designing eval cases, running them via the Codex evals framework, and iterating on skill quality based on results. A must-read for anyone shipping agent skills to production.
Skyscanner integrated Codex CLI with JetBrains IDEs via MCP, enabling in-IDE AI assistance for debugging, test generation, and development workflows without switching to a separate tool. The post details their MCP server setup, the JetBrains plugin integration, and productivity gains observed across the engineering team. A solid real-world MCP adoption case study.
OpenAI's year-end retrospective for developers covering the biggest model, API, and platform milestones of 2025 — from the Responses API launch to Codex, GPT-5.4, Realtime API, and the shift toward production-grade agentic systems. A useful reference for understanding where the platform stands heading into 2026.
OpenAI released new audio model snapshots and expanded Custom Voices access to production voice apps. The updates improve speech quality and latency in the Realtime API and make it easier to deploy branded voices in customer-facing products. Key update for teams building voice agents or voice-first interfaces.
OpenAI breaks down what separates good ChatGPT apps from great ones — focusing on how to design capabilities that genuinely improve conversations rather than just adding features. Covers UX principles, capability scoping, and common pitfalls from the ChatGPT Apps SDK team. Practical guidance for anyone building on the Apps SDK.
Dagster Labs shares how they use Codex across their open-source projects to accelerate documentation — generating docs from code, translating content across formats, and measuring doc completeness automatically. A practical case study showing Codex applied to developer tooling maintenance rather than greenfield code generation.
OpenAI used Codex internally to build experiences, demos, and products for their DevDay 2025 event — eating their own cooking at scale. The post reveals which parts of the event infrastructure were Codex-generated and the workflows they used. Interesting as a signal for what Codex can reliably ship in a high-stakes, time-constrained environment.
OpenAI explains the design rationale behind the Responses API — how it unlocks persistent reasoning, hosted tools, and multimodal workflows that the Chat Completions API couldn't cleanly support. The post covers the architectural decisions and use cases it was designed to enable for GPT-5. The canonical reference for understanding why the Responses API exists.
OpenAI's engineering notes on recent Realtime API updates — covering improvements to speech-to-speech latency, turn detection, interruption handling, and session management. Targeted at developers already building with the Realtime API who want to understand the subtle behaviour changes in recent model snapshots.