The Model Context Protocol (MCP) is an open standard that enables AI assistants to securely connect to external data sources and tools. MCP servers provide AI models with context-aware capabilities, such as code analysis, knowledge base lookups, and system introspection.
The Arm MCP Server provides AI assistants with tools and knowledge specifically for Arm architecture development, migration, and optimization. It includes capabilities like container architecture checking, code analysis with LLVM-MCA, and a knowledge base with content from Arm Learning Paths and other documentation.
MCP servers expose multiple tools that AI assistants can invoke. As these tools evolve, you need reliable automated tests to:
Testcontainers is a Python library that provides lightweight, throwaway instances of Docker containers for testing. Instead of mocking your MCP server, you can spin up the actual Docker container, run tests against it, and tear it down automatically.
Testcontainers flow
This approach offers several benefits:
In this Learning Path, you’ll create an integration test suite that:
In this section:
In the next section, you’ll set up your development environment and install the required dependencies.