llm-tools/mcps/dicom_mcp/docs/CAPABILITIES.md

Claude DICOM-MCP Capabilities List

#	What I can do	Module	Possible without the MCP?
1	Find DICOM files in a folder, including subfolders, and tell you what's in them (series, sequence type, manufacturer). Can also just give a count.	dicom_list_files	❌ No — I could list files with bash, but I couldn't read DICOM headers to identify what they are.
2	Find Dixon sequences in a folder and identify which images are water, fat, in-phase, and out-phase.	dicom_find_dixon_series	❌ No — requires both DICOM parsing and domain-specific sequence identification logic.
3	Read the metadata (headers) from a single DICOM file — patient info, study details, scanner settings, geometry, etc. Can also resolve Philips private tags.	dicom_get_metadata	❌ No — DICOM is a binary format. I can't read it with standard text tools.
4	Compare headers side-by-side across 2–10 DICOM files, highlighting what's different.	dicom_compare_headers	❌ No — same reason; I can't parse the binary headers.
5	Query any DICOM tag across all files in a directory, optionally grouped by another tag (e.g. "show me all echo times, grouped by series").	dicom_query	❌ No.
6	Summarise a whole directory — give a high-level overview of what vendors, scanners, sequences, and series are present, with file counts.	dicom_summarize_directory	❌ No.
7	Validate scan parameters (TR, TE, flip angle, etc.) against expected values for a given sequence.	dicom_validate_sequence	❌ No — can't extract the parameters to validate.
8	Analyse a full series for consistency — check that all files in a series have matching parameters and that the series is complete.	dicom_analyze_series	❌ No.
9	Search for files matching specific criteria using a filter language — text matching, numeric comparisons, or presence checks on any tag.	dicom_search	❌ No.
10	Read Philips private tags by DD number and element offset, or list all private creator blocks in a file.	dicom_query_philips_private	❌ No — these are vendor-specific proprietary tags buried in private DICOM groups.
11	Extract pixel statistics from an image — min, max, mean, standard deviation, percentiles, and optionally a histogram. Can focus on a specific rectangular region.	dicom_read_pixels	❌ No — pixel data is encoded in the DICOM binary.
12	Compute signal-to-noise ratio by placing two regions of interest (signal and noise) on an image.	dicom_compute_snr	❌ No.
13	Render a DICOM image to PNG with adjustable windowing and optional ROI overlays — this is how I showed you those three images.	dicom_render_image	❌ No — I have no way to decode DICOM pixel data and produce a viewable image.
14	Dump the full DICOM tree — show the entire hierarchical structure of a file including nested sequences, with configurable depth.	dicom_dump_tree	❌ No.
15	Compare UID sets between two directories — find which series/studies/instances are shared, missing, or extra.	dicom_compare_uids	❌ No.
16	Verify segmentation references — check that segmentation DICOM files correctly point back to their source images.	dicom_verify_segmentations	❌ No.
17	Analyse inversion times from MOLLI/NOLLI T1 mapping sequences — extract TI values across vendors (handling Philips private tags automatically), flag gaps, and show the acquisition order.	dicom_analyze_ti	❌ No.

All 17 modules live under dicom_mcp/tools/ and are registered via the @mcp.tool() decorator at server startup. In short: none of these capabilities exist without the MCP. DICOM is a complex binary medical imaging format. Without the MCP, I can see that .dcm files exist, but I can't open, read, interpret, or visualise any of them. The MCP turns me from "completely DICOM-blind" into something that can meaningfully inspect, compare, and analyse medical imaging data across vendors.