Why Scaling MCP Beyond Local Dev Creates Serious Enterprise Governance Challenges

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The Model Context Protocol (MCP) allows developers to connect AI models to tools and data quickly, making it popular for local development workflows. However, when organizations attempt to roll out MCP at enterprise scale, significant problems emerge around security, visibility, and governance. Hardcoded credentials, untracked server instances, and overly broad permissions granted to AI agents can expose organizations to serious risks. Platform and security teams struggle to audit which users, models, and tools are involved in any given operation when MCP servers are managed independently across teams. Experts argue that enterprise-scale MCP deployments require a dedicated gateway layer with centralized identity management, observability, and governance controls.

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ProgrammingDEV Community ·

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