OctoPerf MCP Server
Summary
The rise of MCP is reshaping how AI interacts with technical tools, and this project shows how an MCP server can let AI assistants operate OctoPerf directly.
The goal is to make performance testing more accessible: running tests, analyzing results, and generating insights through natural language.
Built as an MVP, the server demonstrates how AI can automate workflows that normally require manual navigation and correlation.
The project highlights MCP’s key concepts, the supporting Go framework, and how developers can extend the system with new tools and analyses.
A demo illustrates end-to-end usage, from listing workspaces to running tests and comparing results.
The experience confirms how MCP can bridge AI and APIs to create smarter, more productive performance-testing workflows.
Table of Contents
- Introduction
- Project Overview
- MVP Approach and Technical Foundations
- Model Context Protocol (MCP) Explanation
- Dev Container Configuration
- Project Architecture
- Demo
- Conclusion