photographi-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| logging | {} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| extensions | {
"io.modelcontextprotocol/ui": {}
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| photographi_analyze_photoA | Analyzes a single photo for technical quality (sharpness, exposure, noise, etc.). Returns overall score, judgement, and per-metric breakdowns. Use this for detailed inspection of individual images. For batch analysis, use photographi_analyze_folder. |
| photographi_analyze_folderA | Batch analyzes all images in a folder with high concurrency (4-8 images at once). Returns quality scores and judgements for each image. Default limit is 100 images per call. Use 'limit' and 'offset' for pagination. If 'nextOffset' is in the response, call again with that offset. Perfect for understanding the overall quality distribution of a shoot. |
| photographi_rank_photographsA | Ranks photos by technical quality and returns the top_n best images. Uses high concurrency to process up to 100 images per call (default limit). Ideal for burst sequences or finding hero shots. Returns detailed metrics for each top image. For full folder analysis, use photographi_analyze_folder instead. |
| photographi_cull_photographsA | Culls low-quality images by moving them to a 'culled_photos' subfolder. Images ABOVE the threshold (default 0.4) stay in the original folder. Images BELOW the threshold are moved to culled_photos/. Processes 100 images per call by default. Use 'limit' and 'offset' for pagination. Mode options: 'move' (default), 'xmp' (sidecar tagging), or 'both'. |
| photographi_threshold_cullA | Binary threshold culling: moves images below min_confidence (default 0.6) to a 'rejects' subfolder. Images ABOVE the threshold stay in the original folder. Similar to photographi_cull_photographs, but uses a higher default threshold and 'rejects/' folder name for stricter filtering. Processes 100 images per call. Mode options: 'move', 'xmp', or 'both'. |
| photographi_get_color_paletteA | Extracts a representative color palette from a single image using K-Means clustering. Returns a list of hex color codes (e.g., ['#FF5733', '#33FF57', ...]). Default is 5 colors. Use this for design inspiration or color grading reference. |
| photographi_get_scene_contentA | Detects objects in a photo using YOLO (e.g., person, dog, car, etc.). Returns a simple list of object labels. Use this for quick scene indexing or content-based search. For full quality analysis with subject-aware metering, use photographi_analyze_photo. |
| photographi_get_folder_palettesB | Extracts color palettes from multiple images in a folder. Processes 20 images per call by default. Use 'limit' and 'offset' for pagination. Returns a map of filename → color palette. Useful for building color-based galleries or moodboards. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 8 tools
Most tools have distinct purposes, but 'cull_photographs' and 'threshold_cull' are very similar, differing only in default thresholds and folder names, which could cause misselection. 'rank_photographs' and 'analyze_folder' also have overlapping functionality.
All tools share the 'photographi_' prefix and generally follow a verb_noun pattern. However, 'cull_photographs' and 'threshold_cull' are inconsistent in structure (verb_noun vs adjective_verb), breaking the otherwise predictable naming convention.
With 8 tools covering analysis, culling, ranking, color extraction, and scene detection, the count is well-scoped for a photography MCP server. Each tool serves a clear role without being excessive or insufficient.
The tool set covers core photography workflows: single/batch analysis, culling, ranking, color palettes, and object detection. Minor gaps exist (e.g., no tool for metadata extraction or direct editing), but these are acceptable for the server's stated purpose.