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CodeGuardian: a Model Context Protocol Server for AI-Assisted Code Quality Analysis and Security Scanning
CodeGuardian is an MCP server that extends AI coding assistants with comprehensive code quality and security analysis capabilities. By implementing eleven specialized tools, CodeGuardian enables developers to access enterprise-grade analysis directly through their AI assistant, eliminating context-switching and reducing friction in adopting secure coding practices.
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Building a Least-Privilege AI Agent Gateway for Infrastructure Automation with MCP, OPA, and Ephemeral Runners
This article presents a least-privilege AI Agent Gateway that places clear controls between AI agents and infrastructure. Agents do not access infrastructure APIs directly. Instead, every request is validated, authorized using policy as code with Open Policy Agent (OPA), and executed in short-lived, isolated environments, with built-in observability using OpenTelemetry.
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NextGen Search - Where AI Meets OpenSearch through MCP
In this article, authors Srikanth Daggumalli and Arun Lakshmanan discuss next-generation context-aware conversational search using OpenSearch and AI agents powered by Large Language Models (LLMs) and Model Context Protocol (MCP).
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MCP: the Universal Connector for Building Smarter, Modular AI Agents
In this article, the authors discuss Model Context Protocol (MCP), an open standard designed to connect AI agents with tools and data they need. They also talk about how MCP empowers agent development, and its adoption in leading open-source frameworks.