Kamya Shah

Compare the top open-source MCP gateways for self-hosted AI infrastructure on performance, governance, token efficiency, and deployment flexibility in 2026. Teams running production AI agents in 2026 are increasingly choosing open-source MCP gateways for self-hosted AI infrastructure rather than managed services. The reasons are practical: data residency requirements, latency sensitivity

A complete guide to MCP gateways for enterprise AI teams: requirements, security risks, governance patterns, and how Bifrost delivers production-grade MCP infrastructure. Enterprise AI teams are deploying agents that read repositories, query databases, hit internal APIs, and execute actions on behalf of users. The infrastructure that makes this safe at

An MCP gateway centralizes tool discovery, routing, governance, and execution for AI agents. Learn how Bifrost's MCP gateway powers production-grade agent infrastructure. As AI agents move from prototypes to production, teams quickly discover that connecting models to external tools is harder than it looks. An MCP gateway solves

Compare the top MCP gateways for production AI agents in 2026 on performance, governance, audit, and tool orchestration capabilities for enterprise AI workloads. The Model Context Protocol (MCP) has shifted from a December 2024 specification to the default integration layer for production AI agents. By March 2026, MCP crossed 97

Compare the best MCP gateways for Claude Code in 2026 on token efficiency, governance, transport support, and production readiness for engineering teams. Claude Code has become a default terminal-based coding agent for engineering teams, and its native support for the Model Context Protocol (MCP) lets it reach into filesystems, databases,