dfxm-geo-mcp
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@dfxm-geo-mcpfind reflections for Ge sample at 15 keV"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.

Run
uvx dfxm-geo-mcpClaude 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.
Related MCP server: axiomatic-mcp
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.
This server cannot be deployed
Maintenance
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