Arm MCP Server
MCP serverDev toolsYour AI can help you move code to Arm processors, make it run better on Arm hardware, and answer questions about how Arm architecture works. This is Arm's official integration for code migration, optimization, and architecture guidance.
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What your AI can do with it
- Migrate code to run on Arm processors
- Optimize code for better performance on Arm hardware
- Answer questions about Arm architecture
- Plan the steps for moving a project to Arm
- Suggest changes that make code faster on Arm
Getting started
- Save this item in Your setup as a reference.
- Read the source or reference documentation for its setup requirements. Saving it here does not connect it to your AI.
- Check this page for availability before trying to install it through Ahel.
From the project's README
As published by arm/mcp in README.md.
An MCP server providing AI assistants with tools and knowledge for Arm architecture development, migration, and optimization.
Using the Arm MCP Server
If your goal is to migrate an application from x86 to Arm as quickly as possible, start here:
Automate x86-to-Arm application migration using Arm MCP Server
Features
This MCP server equips AI assistants with specialized tools for Arm development:
- Knowledge Base Search: Semantic search across Arm documentation, learning resources, intrinsics, and software compatibility information
- Code Migration Analysis: Scan codebases for Arm compatibility using migrate-ease (supports C++, Python, Go, JavaScript, Java)
- Container Architecture Inspection: Check Docker image architecture support using integrated Skopeo and check-image tools.
- Assembly Performance Analysis: Analyze assembly code performance using LLVM-MCA
Pre-Built Image
If you would prefer to use a pre-built, multi-arch image, the official image can be found in Docker Hub here: armlimited/arm-mcp:latest
Prerequisites
- Docker with Buildx support
- An MCP-compatible AI assistant client (e.g. GitHub Copilot, Kiro CLI, Codex CLI, Claude Code, etc)
Quick Start
1. Build the Docker Image
From the root of this repository:
docker buildx build -f mcp-local/Dockerfile -t armlimited/arm-mcp . --load
This builds for the Docker host's native architecture. The release workflow is responsible for explicit multi-architecture builds.
2. Configure Your MCP Client
Choose the configuration that matches your MCP client:
Claude Code
Add to .mcp.json in your project:
{
"mcpServers": {
"arm-mcp": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"--pull=always",
"-v", "/path/to/your/workspace:/workspace",
"armlimited/arm-mcp"
]
}
}
}
GitHub Copilot (VS Code)
Add to .vscode/mcp.json in your project, or globally at ~/Library/Application Support/Code/User/mcp.json (macOS):
{
"servers": {
"arm-mcp": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"--pull=always",
"-v", "/path/to/your/workspace:/workspace",
"armlimited/arm-mcp"
]
}
}
}
The easiest way to open this file in VS Code for editing is command+shift+p and search for
MCP: Open User Configuration
AWS Kiro CLI
Add to ~/.kiro/settings/mcp.json:
{
"mcpServers": {
"arm-mcp": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"--pull=always",
"-v", "/path/to/your/workspace:/workspace",
"armlimited/arm-mcp"
],
"timeout": 60000
}
}
}
Gemini CLI
It is recommended to use a project-local configuration file to ensure the relevant workspace is mounted.
Add to .gemini/settings.json in your project root:
{
"mcpServers": {
"arm-mcp": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"--pull=always",
"-v", "/path/to/your/workspace:/workspace",
"armlimited/arm-mcp"
]
}
}
}
MCP Clients using TOML format (e.g. Codex CLI)
[mcp_servers.arm-mcp]
command = "docker"
args = [
"run",
"--rm",
"-i",
"--pull=always",
"-v", "/path/to/your/workspace:/workspace",
"armlimited/arm-mcp"
]
Note: Replace /path/to/your/workspace with the actual path to your project directory that you want the MCP server to access.
3. Restart Your MCP Client
After updating the configuration, restart your MCP client to load the Arm MCP server.
Logging
Depending on usage, the server may write two log files under /workspace. With the
configuration examples above, these files appear in the project directory on
your computer:
mcp-traffic.jsonlrecords when tools are used, the inputs provided, and the reason for each tool call. It also records results from knowledge base searches.error_logging.yamlrecords details about errors encountered by the server. This information can help with troubleshooting.
These logs may contain information from your project and tool requests. Review their contents before sharing them.
Development and contributing
See CONTRIBUTING.md for repository structure, integration testing, reproducible build inputs, runtime-egress validation, dependency updates, and release workflows.
Troubleshooting
Accessing the Container Shell
To debug or explore the container environment:
docker run --rm -it --entrypoint /bin/bash armlimited/arm-mcp
Common Issues
- Timeout errors during migration scans: Increase the
timeoutvalue in your MCP client configuration (e.g.,"timeout": 120000for 2 minutes) - Empty workspace: Ensure your volume mount path is correct and the directory exists
- Architecture mismatches: Confirm that the local image matches the Docker host's native architecture; use the release workflow for explicit cross-platform builds.
License
Copyright © 2026, Arm Limited and Contributors. All rights reserved.
Licensed under the Apache License, Version 2.0. See LICENSE for details.
Signals
- GitHub stars
- 91
- Forks
- 20
- Last commit
- Oct 2026
Advanced
- Delivery
- arm-mcp MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
- Item type
- mcp-server
- Key
io-github-arm-arm-mcp- Source
- github.com/arm/mcp