MCP Gateway

TL;DR As AI agents move from prototypes to production, MCP gateways have become critical infrastructure for managing tool access at scale. This guide evaluates five leading MCP gateways for teams that prioritize low latency and high throughput: Bifrost leads with 11-microsecond overhead at 5,000 RPS and unified LLM

The Model Context Protocol (MCP), introduced by Anthropic in late 2024, has rapidly become the standard interface for connecting AI models to external tools, APIs, and data sources. As agentic AI workloads move from prototypes into production, the challenge shifts from connecting a single MCP server to managing dozens of

TL;DR MCP gateways have become essential infrastructure for deploying AI agents at scale, providing centralized authentication, observability, and tool governance between agents and external services. This article compares five leading MCP gateway platforms: Bifrost, Docker MCP Gateway, TrueFoundry, Kong AI Gateway, and Lasso Security, each serving distinct production needs

The Model Context Protocol (MCP) is rapidly becoming the standard interface for connecting AI models to external tools, APIs, and data sources. As enterprises scale agentic AI deployments, with Gartner projecting that 40% of enterprise applications will embed autonomous AI agents by the end of 2026, the need for a

The Model Context Protocol (MCP), introduced by Anthropic in late 2024, has become the universal standard for AI agent-to-tool connectivity. Now adopted by OpenAI, Google, and Microsoft, MCP defines how LLM applications discover and interact with external tools, data sources, and workflows through a standardized interface. But the protocol alone

The Model Context Protocol (MCP), introduced by Anthropic in late 2024, has become the de facto standard for connecting AI models to external tools, data sources, and services. As agentic AI workflows move into production, engineering teams need more than a basic MCP client integration. They need a production-grade MCP