Kamya Shah

Kamya Shah

Enterprise MCP Gateway for AI Agents: Best Platform in 2026

Enterprise MCP Gateway for AI Agents: Best Platform in 2026

An MCP gateway controls which AI agent can reach which tool, under whose identity. This guide compares five MCP gateways for enterprise AI agents, including Bifrost, Kong, and AWS AgentCore, on tool scoping, per-user OAuth, and Code Mode's 92.8% input-token reduction.

Top AI Security Tools in 2026: 8 Platforms Compared

Top AI Security Tools in 2026: 8 Platforms Compared

This guide compares eight platforms across runtime guardrails, posture management, model scanning, red teaming, and data security.

Enterprise AI Observability Tools in 2026: Top 5 Platforms Compared

Enterprise AI Observability Tools in 2026: Top 5 Platforms Compared

Enterprise AI observability works best as a two-layer stack: a gateway that captures every model request and a backend your SREs already run. This guide compares Bifrost, Datadog, Dynatrace, Grafana Cloud, and Elastic on coverage, cost attribution, data control, and deployment.

Top 5 MCP Gateways for Built-in Routing and Control

Top 5 MCP Gateways for Built-in Routing and Control

MCP gateway routing decides which server handles each tool call; control decides whether the agent may make it. This guide compares Bifrost, Kong, Docker, Microsoft MCP Gateway, and Lasso on both

What is an MCP Gateway? Key Features and Benefits

What is an MCP Gateway? Key Features and Benefits

TL;DR * An MCP gateway is a single control plane between AI models and MCP servers that handles tool discovery, routing, authentication, governance, and execution from one endpoint. * Without a gateway, every agent configures its own MCP servers, credentials, and approval rules, which creates configuration sprawl, token bloat, and no

Top 5 Enterprise LLM Gateways for Cost Control and Failover

Top 5 Enterprise LLM Gateways for Cost Control and Failover

TL;DR * An enterprise LLM gateway centralizes routing, budgets, caching, failover, and usage attribution for every service that calls a model provider. * Cost control at the gateway comes mainly from caching and model routing; budgets and per-key model limits bound the bill, and attribution is what makes those decisions

Why Your AI Stack Needs an MCP Gateway

Why Your AI Stack Needs an MCP Gateway

TL;DR * An MCP gateway is a control layer between AI agents and MCP servers that centralizes authentication, tool discovery, access control, credential management, and audit logging behind one endpoint. * Direct agent-to-server connections create N×M credential sprawl, no central policy, and no unified record of tool calls