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Load testing hosted MCP servers with Locust and Azure Load Testing
A new reusable Python harness allows developers to load test Model Context Protocol (MCP) servers using Locust and Azure Load Testing.
What: The framework models the full lifecycle of an MCP server—including initialization, tool discovery, and authentication—to help SREs measure latency and concurrency behavior under heavy AI agent workloads.
Why it matters: As MCP becomes a standard for connecting AI agents to external tools, infrastructure teams need to proactively test these endpoints for stability before they are overwhelmed by automated requests.
Decoder
- MCP (Model Context Protocol): An open standard for connecting AI assistants to systems, databases, and internal tools.
Original article
This guide demonstrates how to load test hosted MCP servers using a reusable Python and Locust harness that faithfully models the MCP lifecycle, including initialization, tool discovery, tool calls, authentication, and session cleanup. The framework supports stateful and stateless MCP servers, multiple authentication patterns, and seamless execution both locally and in Azure Load Testing, enabling teams to measure latency, concurrency behavior, and failure characteristics of production MCP endpoints under realistic AI agent workloads.
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