Arm MCP Server LP

content/learning-paths/servers-and-cloud-computing/arm-mcp-server/1-overview.md

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+---
+title: Arm MCP Server Overview
+weight: 2
+
+### FIXED, DO NOT MODIFY
+layout: learningpathall
+---
+
+## What is the Arm MCP Server?
+
+The Arm MCP Server is a tool that enables AI-powered developer tools to become Arm cloud migration and optimization experts. It implements the Model Context Protocol (MCP), an open standard that allows AI assistants to access external tools and data sources.
+
+By connecting your AI coding assistant to the Arm MCP Server, you gain access to Arm-specific knowledge, container image inspection tools, and code analysis capabilities that streamline the process of migrating applications from x86 to Arm.
+
+## How to interact with the Arm MCP Server
+
+There are multiple ways to interact with the Arm MCP Server, depending on your development environment and workflow:
+
+### 1. Direct AI Chat
+
+You can ask your AI assistant natural language questions, and it will automatically use the MCP tools when appropriate. For example:
+
+```text
+Check if the nginx:latest Docker image supports Arm architecture
+```
+
+### 2. Prompt Files
+
+Many AI coding tools support prompt files that provide structured instructions. These files can reference MCP tools and guide the AI through complex workflows like full codebase migrations.
+
+### 3. Agentic Workflows
+
+Tools like GitHub Copilot Agent Mode, Claude Code, Kiro, and OpenAI Codex support autonomous agent workflows where the AI can execute multi-step migration tasks with minimal intervention. These fully agentic workflows can be combined with prompt files and direct chat to create an extremely powerful development system.
+
+## Available Arm MCP Server Tools
+
+The Arm MCP Server provides several specialized tools for migration and optimization:
+
+### knowledge_base_search
+
+Searches an Arm knowledge base of learning resources, Arm intrinsics, and software version compatibility using semantic similarity. Given a natural language query, it returns matching resources with URLs, titles, and content snippets ranked by relevance.
+
+**Use case:** Finding documentation, tutorials, or version compatibility information for Arm migration.
+
+### check_image
+
+Checks Docker image architectures. Provide an image in `name:tag` format and get a report of supported architectures.
+
+**Use case:** Quickly verify if a container base image supports `arm64` before starting a migration.
+
+### skopeo
+
+A container image architecture inspector that inspects container images remotely without downloading them to check architecture support (especially ARM64 compatibility).
+
+**Use case:** Detailed inspection of container manifests and multi-architecture support before migrating workloads to Arm-based infrastructure.
+
+### migrate_ease_scan
+
+Runs a migrate-ease scan against a workspace or remote Git repository. Supported scanners include: cpp, python, go, js, and java. Returns analysis results identifying x86-specific code that needs attention.
+
+**Use case:** Automated scanning of codebases to identify architecture-specific dependencies, build flags, intrinsics, and libraries that need to be changed for Arm.
+
+### mca (Machine Code Analyzer)
+
+An assembly code performance analyzer that predicts performance on different CPU architectures and identifies bottlenecks. It estimates Instructions Per Cycle (IPC), execution time, and resource usage.
+
+**Use case:** Analyzing and optimizing performance-critical assembly code when migrating between processor types.
+
+### sysreport_instructions
+
+Provides instructions for installing and using sysreport, a tool that obtains system information related to system architecture, CPU, memory, and other hardware details.
+
+**Use case:** Understanding the target Arm system's capabilities before deployment.
+
+## Setting up the Arm MCP Server
+
+To use the Arm MCP Server with your AI coding assistant, you need to configure your tool to connect to the server. The exact configuration depends on your tool:
+
+[placeholder list of links to learn.arm.com install guides]
+
+Continue to the next section to see the Arm MCP Server in action.

content/learning-paths/servers-and-cloud-computing/arm-mcp-server/2-docker-check.md

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+---
+title: Direct AI Chat
+weight: 3
+
+### FIXED, DO NOT MODIFY
+layout: learningpathall
+---
+
+## Checking Base Images for Arm Compatibility
+
+This section demonstrates just one example of using direct AI chat with the Arm MCP Server. You can use similar natural language prompts to check library compatibility, search for Arm documentation, or analyze code for migration issues.
+
+One of the first steps in migrating a containerized application to Arm is verifying that your base images support the `arm64` architecture. The Arm MCP Server makes this easy with a simple natural language prompt.
+
+## Example: Legacy CentOS 6 Application
+
+Consider an application built on CentOS 6, a legacy distribution that has reached end-of-life. Here's a Dockerfile that represents a typical x86-optimized compute benchmark application. Copy it to your VS Code with GitHub Copilot or other agentic IDE:
+
+```dockerfile
+FROM centos:6
+
+# CentOS 6 reached EOL, need to use vault mirrors
+RUN sed -i 's|^mirrorlist=|#mirrorlist=|g' /etc/yum.repos.d/CentOS-Base.repo && \
+    sed -i 's|^#baseurl=http://mirror.centos.org|baseurl=http://vault.centos.org|g' /etc/yum.repos.d/CentOS-Base.repo
+
+# Install EPEL repository (required for some development tools)
+RUN yum install -y epel-release && \
+    sed -i 's|^mirrorlist=|#mirrorlist=|g' /etc/yum.repos.d/epel.repo && \
+    sed -i 's|^#baseurl=http://download.fedoraproject.org/pub/epel|baseurl=http://archives.fedoraproject.org/pub/archive/epel|g' /etc/yum.repos.d/epel.repo
+
+# Install Developer Toolset 2 for better C++11 support (GCC 4.8)
+RUN yum install -y centos-release-scl && \
+    sed -i 's|^mirrorlist=|#mirrorlist=|g' /etc/yum.repos.d/CentOS-SCLo-scl.repo && \
+    sed -i 's|^mirrorlist=|#mirrorlist=|g' /etc/yum.repos.d/CentOS-SCLo-scl-rh.repo && \
+    sed -i 's|^# baseurl=http://mirror.centos.org|baseurl=http://vault.centos.org|g' /etc/yum.repos.d/CentOS-SCLo-scl.repo && \
+    sed -i 's|^# baseurl=http://mirror.centos.org|baseurl=http://vault.centos.org|g' /etc/yum.repos.d/CentOS-SCLo-scl-rh.repo
+
+# Install build tools
+RUN yum install -y \
+    devtoolset-2-gcc \
+    devtoolset-2-gcc-c++ \
+    devtoolset-2-binutils \
+    make \
+    && yum clean all
+
+# Set working directory
+WORKDIR /app
+
+# Copy all header files
+COPY *.h ./
+
+# Copy all C++ source files
+COPY *.cpp ./
+
+# Build the application with optimizations using devtoolset-2 (GCC 4.8)
+# AVX2 intrinsics are used in the code for x86-64 platforms
+RUN scl enable devtoolset-2 "g++ -O2 -mavx2 -o benchmark \
+    main.cpp \
+    matrix_operations.cpp \
+    hash_operations.cpp \
+    string_search.cpp \
+    memory_operations.cpp \
+    polynomial_eval.cpp \
+    -std=c++11"
+
+# Create a startup script
+COPY start.sh .
+RUN chmod +x start.sh
+
+# Run the application
+CMD ["./start.sh"]
+```
+
+This Dockerfile has several x86-specific elements:
+- The `centos:6` base image
+- The `-mavx2` compiler flag for x86 AVX2 SIMD instructions
+- C++ source files containing x86 intrinsics (which you will examine in the next section)
+
+## Using the Arm MCP Server to Check Compatibility
+
+With the Arm MCP Server connected to your AI assistant, you can check the base image compatibility with a simple prompt:
+
+```text
+Check this base image for Arm compatibility
+```
+
+The AI assistant will use the `check_image` or `skopeo` tool to inspect the image and return a report. For `centos:6`, you would discover that this legacy image does **not** support `arm64` architecture.
+
+This simple interaction demonstrates how direct AI chat can quickly surface compatibility issues. In the next section, you'll see how to resolve these issues automatically using a fully agentic migration workflow with prompt files.