5 posts tagged with "Best Practices"

AI agents now access your codebases, databases, and production systems with unprecedented autonomy. Yet most organizations lack visibility into what these agents do—or the controls to stop risky actions before they execute. With 45% of enterprises running production AI agents that have critical system access, security teams face a new challenge: governing autonomous tools that make real-time decisions without human approval.

This guide outlines eight security best practices for enterprise teams deploying AI agents at scale—covering everything from foundational security architecture to transforming local development into production-grade services.

Claude Code operates directly in developers' terminals with the same permissions as the user—reading files, executing commands, and accessing production systems through MCP tools. Without proper governance, organizations cannot see what these agents access or control their actions. Enterprises need comprehensive security controls that include permission management, network isolation, audit logging, and compliance frameworks to protect sensitive code and intellectual property. An LLM Proxy provides essential visibility and control over how Claude Code and other coding agents interact with your systems, transforming shadow AI into sanctioned AI while maintaining developer productivity.

This article outlines actionable strategies for securing Claude Code deployments, covering enterprise configuration, risk mitigation, compliance alignment, and operational monitoring to ensure both security and development velocity.

Cursor's rapid adoption as an AI-powered code editor has seen rapid enterprise adoption, including tens of thousands of enterprises and more than half of the Fortune 500—but recent critical vulnerabilities demonstrate that enterprise deployment requires robust security controls beyond default settings. With coding agents gaining extensive system access to read files, execute commands, and connect to production systems through MCP tools, organizations need centralized governance to maintain visibility and control over agent behavior. This guide provides actionable strategies for securing Cursor deployments, from immediate configuration hardening to enterprise-grade compliance frameworks.

With 71% of companies now using generative AI in at least one business function, Cursor IDE enables organizations to access external data through Model Context Protocol servers. Yet over half (53%) of MCP servers rely on static API keys or Personal Access Tokens (PATs)—long-lived credentials that are rarely rotated and are high-impact if leaked. Recent critical vulnerabilities (CVE-2025-54136) expose remote code execution pathways, creating urgent pressure to secure MCP deployments before compliance teams block adoption. The MintMCP Gateway provides SOC 2 Type II certified infrastructure that transforms local MCP servers into production-ready services with centralized authentication, real-time monitoring, and compliance-ready audit trails—enabling enterprises to deploy AI coding assistants without creating shadow IT risks.

This article outlines actionable security configurations for Cursor's MCP server integration, covering client-side protections, enterprise gateway deployment, access controls, compliance requirements, and monitoring practices to ensure both security and operational efficiency.

Custom actions let ChatGPT call your HTTP endpoints. They are ChatGPT's version of tool access, similar to Model Context Protocol (MCP). However, there are some important things to note while building for ChatGPT custom actions. We share what we learned here to help you design actions that behave well in chat.