Rate Limiting MCP Servers Prevents API Overload, Crashes, and Runaway Costs

Model Context Protocol (MCP) servers without request controls are vulnerable to denial-of-service attacks, memory exhaustion, and excessive API charges. Because LLMs automatically retry failed requests, an uncontrolled loop of MCP tool calls can rapidly consume system resources or inflate costs. Rate limiting addresses this by capping the number of requests an agent can make to an MCP server within a defined time window. A practical implementation can be achieved using Agentgateway on a Kubernetes cluster, with the GitHub Copilot MCP Server serving as a demonstration target. The setup involves configuring a gateway policy that defines request thresholds, helping teams safeguard infrastructure from both accidental and malicious overload.