Microsoft Azure DevOps MCP Server
Microsoft has published an open-source Model Context Protocol (MCP) server for Azure DevOps, enabling AI agents to interact directly with Azure DevOps services. The repository is implemented in TypeScript and has accumulated 1,710 GitHub stars. This extends the MCP ecosystem with enterprise DevOps tooling, allowing agents to perform operations such as managing pipelines, work items, and repositories.
Related guides (4)
Related events (8)
Anthropic Open-Sources the Model Context Protocol (MCP)
Anthropic has released the Model Context Protocol (MCP), an open standard enabling secure, two-way connections between AI assistants and external data sources such as business tools, content repositories, and development environments. The protocol introduces a client-server architecture with SDKs, local MCP server support in Claude Desktop, and a repository of pre-built connectors for systems like GitHub, Slack, Google Drive, and Postgres. Early adopters include Block and Apollo, with development tool companies Zed, Replit, Codeium, and Sourcegraph integrating MCP into their platforms. The goal is to replace fragmented, per-source integrations with a single universal protocol, improving context availability for AI agents.
Chrome DevTools MCP Server for Coding Agents
The chrome-devtools-mcp repository exposes Chrome DevTools functionality as a Model Context Protocol (MCP) server, enabling coding agents to interact with browser debugging tools programmatically. The project has accumulated over 40,000 stars on GitHub, with 132 added today, indicating strong community traction. This tooling bridges browser developer tooling with AI agent workflows, allowing agents to inspect, debug, and interact with web pages.
MetaTrader MCP Server: AI LLM Trading via Model Context Protocol
An open-source Python project implementing a Model Context Protocol (MCP) server that enables AI language models to execute trades on the MetaTrader platform. The repository has gained 82 stars in a single day, reaching 408 total. This represents a concrete deployment of the MCP agent-tool pattern in a financial trading context.
MCP for Research: How to Connect AI to Research Tools
Hugging Face published a blog post explaining how the Model Context Protocol (MCP) can be used to connect AI agents to research tools and data sources. The post covers practical patterns for integrating AI with academic and scientific workflows using MCP as a standardized interface layer. This is a commentary/tutorial piece aimed at researchers looking to extend AI agent capabilities into domain-specific tooling.
MCP is Dead? — Community Debate on Model Context Protocol's Viability
A blog post from Quandri's engineering team provocatively questions whether the Model Context Protocol (MCP) is failing or already obsolete, generating significant community discussion on Hacker News with 236 points and 206 comments. The piece appears to critically examine MCP's adoption trajectory and potential shortcomings as a standard for AI agent tool integration. The high engagement suggests meaningful disagreement or concern in the practitioner community about MCP's future as an interoperability layer.
IBM releases mcp-context-forge: AI gateway and proxy for MCP, A2A, and REST/gRPC APIs
IBM has open-sourced mcp-context-forge, a Python-based AI gateway, registry, and proxy that sits in front of MCP, A2A, or REST/gRPC APIs and exposes a unified endpoint with centralized discovery, guardrails, and management. The tool is designed to optimize agent and tool calling workflows and supports plugins. With ~3,800 GitHub stars, it represents a notable infrastructure contribution to the MCP/A2A ecosystem from a major enterprise vendor.
Building the Hugging Face MCP Server
Hugging Face has published a blog post describing the construction of an MCP (Model Context Protocol) server that exposes Hugging Face platform capabilities to AI agents and LLM toolchains. The post covers the architecture and implementation of the server, enabling agents to search models, datasets, and spaces programmatically. This represents Hugging Face's integration into the emerging MCP ecosystem for agent-tool interoperability.
How to Build an MCP Server with Gradio
Hugging Face published a tutorial on building Model Context Protocol (MCP) servers using Gradio, enabling AI models to expose tools and resources through the MCP standard. The post demonstrates how Gradio applications can serve as MCP-compatible backends, allowing AI agents to discover and invoke Gradio-hosted functions. This lowers the barrier for ML practitioners to participate in the emerging MCP ecosystem without deep protocol knowledge.