About Arm MCP Server
Arm MCP Server gives AI assistants tools and reference information for Arm architecture development, migration, and optimization. It combines documentation search with code compatibility scans, container image checks, and assembly performance analysis.
Key features
- 01Search Arm documentation and compatibility information
- 02Scan code for Arm migration compatibility
- 03Inspect Docker image architecture support
- 04Analyze assembly performance with LLVM-MCA
Use cases
- 01Find Arm documentation or intrinsic guidance
- 02Assess a codebase for x86-to-Arm migration
- 03Check a container image's supported architectures
- 04Analyze assembly performance
MCP support
Exposes Arm-focused search, migration analysis, container architecture inspection, and assembly analysis tools to MCP clients. The server runs as a Docker image and is configured in an MCP-compatible client.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEArm MCP Server
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.
For local development builds, see the Quick Local Development Builds section in CONTRIBUTING.md.
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.
Suspected vulnerabilities must not be reported in public issues. See the Arm MCP security policy and report them via Arm PSIRT.
License
Copyright © 2026, Arm Limited and Contributors. All rights reserved.
Licensed under the Apache License, Version 2.0. See LICENSE for details.
Comments
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