#model-context-protocol

#model-context-protocol

MCP gives IDEs and agents a standard way to talk to tools and data. As the docs put it, "Think of MCP like a USB-C port for AI applications," which captures the goal of uniform connectors with minimal client glue. The registry sits above that protocol, publishing a machine-readable catalog of servers that clients can query and install. "We're launching...the MCP Registry-an open catalog and API for publicly available MCP servers," the maintainers wrote in the preview announcement.

OpenAI has added a beta of Developer mode to ChatGPT, enabling full read and write support for MCP (Model Context Protocol) tools, though the documentation describes the feature as dangerous. Developer community lead Edwin Arbus said that "in developer mode, developers can create connectors and use them in chat for write actions (not just search/fetch). Update Jira tickets, trigger Zapier workflows or combine connectors for complex automations." Limitations in the initial beta are that developer mode does not work in Team workspaces or in project chats.

Every time a developer wants their AI agent to use a new tool, like a weather API or a flight booking system, they have to build a custom bridge. It's like needing a different, clunky adapter for every single device you own.

GitLab has launched the public beta of its GitLab Duo Agent Platform, an orchestration tool that enables developers to collaborate asynchronously with AI agents across the DevSecOps lifecycle. The platform, now available to GitLab.com Premium and Ultimate customers as well as self-managed installations, transforms traditional, linear development workflows into dynamic, multi-agent systems where AI handles routine tasks such as refactoring, security scanning, and research, while developers focus on complex problem-solving.

For years, APIs have served as the backbone of data access, but they were never designed with AI in mind. They lack memory, context, and intent awareness-forcing developers to bolt on brittle glue code every time models change. Anthropic's introduction of MCP earlier this year marked a turning point, offering a standardized way to make APIs context-aware and AI-ready. But as Chivukula points out, adopting MCP isn't just about creating a one-off server.

"MCP acts like a secure 'universal adapter' for connecting AI agents (like Copilot) to external tools, databases, code search engines, or deployment pipelines, so there are no more one-off integrations for every service," Walter said.

Wassette is a new open source tool that allows developers to assemble lightweight Model Context Protocol servers using WebAssembly components, enhancing AI-driven functionalities.

The Model Context Protocol (MCP) enhances AI copilots by providing structured tools and context that enable effective task execution, beyond simple prompts.

The Model Context Protocol (MCP) is an open standard that enables large language models to interact with external tools and data through a standardized interface.

Agent Mode combines familiar and novel elements, facilitating three levels of AI collaboration: conversational brainstorming, human-approved code changes, and a near-autonomous coding agent.

Technologies like Model Context Protocol (MCP) are reshaping both how we build AI-powered applications and what we can do with them. MCP makes it easier to add AI features to existing code and services.

CloudBees launched Model Context Protocol Server to enhance its Unify platform, allowing integration of AI agents into DevOps workflows across multiple CI/CD platforms.

Generative AI holds immense potential, yet integrating it into existing workflows remains a challenge without extensive development resources.

PayPal's new Agent Toolkit integrates its API suite with AI frameworks, enabling developers to streamline workflows like order management and invoice generation without complex setups.