A new companion project, xraylib-mcp-server, makes xraylib's X-ray interaction data accessible to AI assistants through the Model Context Protocol (MCP).
This means you can query cross-sections, fluorescence lines, edge energies, scattering factors, and more from MCP-compatible tools like Claude Desktop, Claude Code, VS Code with GitHub Copilot, and others — using natural language.
Examples of what you can ask:
- "What is the K-edge energy of iron?"
- "Calculate the photoionization cross section of SiO2 at 10 keV"
- "Get the Lα1 fluorescence line energy for uranium"
The server exposes 101 tools covering the full breadth of xraylib's database.
For installation and configuration instructions, see the xraylib-mcp-server repository.
A new companion project, xraylib-mcp-server, makes xraylib's X-ray interaction data accessible to AI assistants through the Model Context Protocol (MCP).
This means you can query cross-sections, fluorescence lines, edge energies, scattering factors, and more from MCP-compatible tools like Claude Desktop, Claude Code, VS Code with GitHub Copilot, and others — using natural language.
Examples of what you can ask:
The server exposes 101 tools covering the full breadth of xraylib's database.
For installation and configuration instructions, see the xraylib-mcp-server repository.