As organizations race to implement AI agents, many are building Model Context Protocol (MCP) servers to mediate between Large Language Models (LLMs) and external tools and resources. Among the most crucial challenges in deploying MCP servers is security: the non-deterministic input and output of LLMs create agentic-specific risks such as LLM prompt injection, data exfiltration, execution environment risks, and more.
WebAssembly (Wasm) components provide new real-time security controls to address the MCP security problem. Wasm component binaries are portable, polyglot sandboxes that interact with the outside world via explicitly enabled, language-agnostic interfaces. When MCP servers are compiled to Wasm, they can be deployed with the confidence that agents can only interact with approved tools and resources in approved ways.
In this blog, we'll examine patterns for remote-hosting sandboxed MCP servers, explain how Wasm helps to mitigate security risks associated with AI agent integration, and demonstrate how to deploy a sandboxed MCP server with Wasm using Kubernetes and Cosmonic Control.















