Iflow Mcp Arm Arm
FreeNot checkedArm MCP Server - Provides AI assistants with tools for Arm architecture development, migration, and optimization
About
Arm MCP Server - Provides AI assistants with tools for Arm architecture development, migration, and optimization
README
An Model Context Protocol (MCP) server providing AI assistants with tools and knowledge for Arm architecture development, migration, and optimization.
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
- System Information: Instructions for gathering detailed system architecture information via sysreport
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 for multi-arch builds)
- 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 --platform linux/arm64,linux/amd64 -f mcp-local/Dockerfile -t armlimited/arm-mcp .
For a single-platform build (faster):
docker buildx build -f mcp-local/Dockerfile -t armlimited/arm-mcp . --load
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",
"-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",
"-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",
"-v", "/path/to/your/workspace:/workspace",
"--name", "arm-mcp",
"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",
"-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",
"-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.
Repository Structure
mcp-local/: The MCP server implementationserver.py: Main FastMCP server with tool definitionsutils/: Helper modules for each tooldata/: Pre-built knowledge base (embeddings and metadata)Dockerfile: Multi-stage Docker build
embedding-generation/: Scripts for regenerating the knowledge base from source documents
Integration Testing
Pre-requisites
- Build the mcp server docker image
- Install the required test packages using -
pip install -r tests/requirements.txtwithin themcp_localdirectory.
Testing Steps
- Run the test script -
python -m pytest -s tests/test_mcp.py - Check if following 2 docker containers have started - mcp server & testcontainer
- All tests should pass without any errors. Warnings can be ignored.
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: If you encounter platform-specific issues, rebuild for your specific platform using
--platform linux/amd64or--platform linux/arm64
Contributing
Contributions are welcome! Please feel free to submit issues or pull requests.
When contributing:
- Follow PEP 8 style guidelines for Python code
- Update documentation for any new features or changes
- Ensure the Docker image builds successfully before submitting
License
Copyright © 2025, Arm Limited and Contributors. All rights reserved.
Licensed under the Apache License, Version 2.0. See LICENSE for details.
Installing Iflow Mcp Arm Arm
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/iflow-mcp/arm-mcpFAQ
Is Iflow Mcp Arm Arm MCP free?
Yes, Iflow Mcp Arm Arm MCP is free — one-click install via Unyly at no cost.
Does Iflow Mcp Arm Arm need an API key?
No, Iflow Mcp Arm Arm runs without API keys or environment variables.
Is Iflow Mcp Arm Arm hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Iflow Mcp Arm Arm in Claude Desktop, Claude Code or Cursor?
Open Iflow Mcp Arm Arm on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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