dfxm-geo-mcp
An MCP server that lets an AI client drive the dfxm-geo dark-field X-ray microscopy forward model: validate and scaffold configs, enumerate reachable reflections, and render preview-scale simulations.
!Claude Desktop rendering a DFXM image from a plain-English request
Run
uvx dfxm-geo-mcp
Claude Desktop (claude_desktop_config.json):
{"mcpServers": {"dfxm-geo": {"command": "uvx", "args": ["dfxm-geo-mcp"]}}}
Or: pip install dfxm-geo-mcp then dfxm-geo-mcp.
First run pulls a heavy scientific stack (numba/scipy) and warms a JIT cache (~10 s once). No fake demo mode — the sims are real.
Tools
validate_config · find_reflections · predict_visibility (g·b reflection-visibility ranking; structured scores plus a self-contained .html) · scaffold_config · run_forward (analytic preview; saves a PNG and a self-contained .html) · run_rocking (interactive φ-rocking-curve viewer: a single self-contained .html with a frame scrubber + live rocking-curve plot) · start_bootstrap / get_job_status / get_job_result (MC fidelity).
Both run_forward and run_rocking write self-contained HTML (image(s) embedded, all CSS/JS inline, no external origins) that opens full-size in any browser and is surfaced by file-showing clients.
Architecture
A protocol-agnostic ops layer wrapping dfxm-geo, under a thin FastMCP adapter. See docs/superpowers/specs/.
Roadmap (v2)
run_identify · remote HTTP transport · .mcpb bundle.
<!-- mcp-name: io.github.borgi-s/dfxm-geo-mcp -->
