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Arm MCP Server

Arm architecture migration and optimization tools for AI-driven development workflows.

Data last scanned today · Reviewed today

63★ 91PythonApache-2.0

Overview

This MCP server provides AI assistants with specialized capabilities for Arm-based software development. It enables semantic search across Arm's official documentation and learning resources, facilitating efficient navigation of technical specifications, intrinsics, and compatibility guides. Beyond knowledge retrieval, the server includes practical utilities for code and infrastructure analysis. It can scan codebases for cross-architecture compatibility using migrate-ease, inspect Docker image architectures via Skopeo, and perform assembly performance analysis using LLVM-MCA.

Our verdict

With a security score of 40/100, this server is classified as high-risk. This rating stems primarily from its community-maintained status—meaning it is not officially maintained by the vendor—and the fact that its authentication and read-only mode protocols have not yet been editorially reviewed. It is suitable for developers actively porting applications to Arm who are comfortable with the risks of community-developed software, but it should be avoided in sensitive or automated environments until its security posture is more thoroughly assessed.

Zero direct dependencies reduce potential supply-chain vulnerabilities.
Integrated support for industry-standard tools like Skopeo and LLVM-MCA.
Features a clear, documented path for multi-language code migration.
Active development with commits occurring as recently as today.

Security controls like authentication remain currently unreviewed.
Lack of editorial review regarding read-only operational safety.
Operates as a community project rather than an official Arm offering.

Compatibility

Client	Local	Docker	Remote	Read-only
Claude Desktop
Cursor
VS Code
Windsurf
ChatGPT

Frequently asked questions

›What prerequisites are required to run the Arm MCP Server?

You must have Docker with Buildx support installed and an MCP-compatible AI assistant client such as GitHub Copilot, Kiro CLI, Codex CLI, or Claude Code.

›Does the server require specific filesystem access?

Yes, you must mount your project directory to /workspace in the Docker container so that the tools can access your codebase for migration analysis and logs.

›Where does the server store log files?

The server writes mcp-traffic.jsonl and error_logging.yaml files directly into the mounted /workspace directory on your local machine.

›How can I resolve timeout errors during code migration scans?

You can resolve these by increasing the timeout value in your MCP client's configuration file, for example by setting it to 120000 for a two-minute window.

›What programming languages are supported for migration analysis?

The server's code migration analysis tool supports C++, Python, Go, JavaScript, and Java.

›How can I debug the container environment?

You can access the container shell for exploration by running the Docker image with the --entrypoint /bin/bash flag.