plantcv-mcp server

Read from the package source without running it. The installed server may list more.

• calibrate_scale_from_marker

  Measure a size marker of known real length and return px_per_mm, which you then pass to measure() to get traits in mm instead of pixels.

• correct_lens_distortion

  Correct lens/fisheye distortion using checkerboard calibration photos, write the corrected image next to the input as <image>_undistorted.png (or to output_path, refused if it exists), and return its path plus a preview. Segment, calibrate scale, and measure the CORRECTED file. The correction is never written INTO checkerboard_dir: everything there is read as a calibration frame, so pass output_pa

• count_leaves

  Split ONE top-view plant mask into leaf instances with PlantCV's distance-transform watershed and return the count, each instance's area, centroid [x, y] and bbox [x, y, w, h] (full-frame pixels), and the overlay with every instance outlined and numbered — instance `id` is the number drawn on the picture.

• list_methods

  List available segmentation channels, methods, object types, analyses, and the pinned PlantCV version.

• measure

  Return plant traits for a segmentation produced by segment(). Raises if the mask is degenerate rather than returning zeros.

• measure_imageswrite action

  Run one fixed segmentation recipe across many images.

• measure_morphology

  Skeleton-based traits for ONE plant: per-segment path and euclidean length, curvature, angle, tangent angle and insertion angle, plus stem height/length/angle, tip and branch-point counts, cycles and widths. Returns the numbered-segment overlay with the table — segment `id` is the number drawn on the picture.

• measure_regions

  Measure EACH plant in a multi-plant image separately.

• measure_spectral

  Per requested index: mean, median, std, min, max over the session's mask, computed on the calibrated (or float-cast) cube exactly as segment_hyperspectral() prepared it. indices defaults to the index the session was segmented with. include_spectrum adds the per-band mean/ max/min/std reflectance — hundreds of numbers per list, off by default; band_count is always reported. Refuses RGB and thermal

• measure_thermal

  max, min, mean and median degrees Celsius over the session's mask, via PlantCV's analyze.thermal, plus the pixel count and the frame's range. include_histograms adds the 100-bin temperature histogram. Refuses RGB and hyperspectral sessions.

• refine

  Apply morphological cleanup to a session's mask and get a NEW session.

• segment

  Segment an image. Returns the overlay image and mask diagnostics — NOT traits. Use the returned session_id with measure() to get traits.

• segment_hyperspectral

  Compute one spectral index over an ENVI cube (.raw/.hdr pair; give either path) and threshold it into a mask, returning the overlay on the cube's pseudo-RGB plus diagnostics — NOT numbers. Use the session_id with measure_spectral().

• segment_leaves_sam

  Split ONE top-view plant mask into leaf instances with Segment Anything (ViT-B, Apache-2.0) and return the count, each instance's area, centroid [x, y] and bbox [x, y, w, h] (full-frame pixels), and the overlay with every instance outlined and numbered, as count_leaves() does. The model is prompted on a 32x32 point grid restricted to the mask; masks are kept when leaf-sized (0.2%-40% of the plant)

• segment_thermal

  Read a FLIR radiometric .jpg (via flyr), a .csv, or a .npz of degrees Celsius and select the pixels between min_c and max_c (give at least one) as the plant. Returns the overlay on a grey rendering of the frame, the frame's temperature range and diagnostics — NOT numbers; use the session_id with measure_thermal(). A thermal frame is a different sensor from the RGB camera, so a mask is never borrow

• suggest_segmentation

  Return colourspace and threshold contact sheets, plus what each object_type would yield on this image, so the channel/method/polarity choice is informed rather than blind. Call this before segment(). polarity.warnings carries `noisy_segmentation` when the recommended polarity is many components with no dominant one — background texture, not a plant — which the `ambiguous` flag alone cannot tell yo

• Code scan23 source files scanned20/25
• –Live reliabilityno gateway calls yet and no remote to proben/a
• –Tool poisoningtools not inspected (local package is not executed); not countedn/a
• Auth qualitylocal package, no credentials required12/15
• Maintenancelast push 0 days ago15/15
• Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

plantcv-mcp: common questions

Is plantcv-mcp server safe?

Yes, by our scan: it is graded A (85/100). Read the plantcv-mcp safety report

How do I install plantcv-mcp?

It runs on your machine. Copy the Claude Code, Claude Desktop or Cursor config from the install section.

Does plantcv-mcp need an API key?

Not as far as the registry entry and our scan can tell: no credentials are declared or required.

Is plantcv-mcp maintained?

The last commit was in the last day (2026-09-19). The latest release is v1.15.0.