AI Image Metadata Cleaner
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": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| inspect_image_metadataA | Inspects an image for AI detection risks, C2PA manifests, and EXIF footprints. Args: image_path: Absolute or relative path to the image file. Returns: Diagnostic audit detailing C2PA presence, keywords, and AI risk level. |
| strip_metadata_onlyA | Strips all metadata, C2PA manifests, and EXIF tags without modifying pixels. Args: image_path: Path to the input image file. output_path: Optional path for cleaned output image. quality: JPEG/WebP compression quality (1-100, default 95). Returns: Summary of cleaned image and stripped markers. |
| anti_ai_sanitizeA | Full anti-AI pipeline: strips C2PA/EXIF, disrupts lattices/watermarks, and adds camera physics. Args: image_path: Path to the target AI image. output_path: Optional path to save sanitized image. Defaults to '_sanitized.jpg'. camera_profile: Camera profile to inject ('none', 'iphone_15_pro', 'sony_a7iv', 'samsung_s24_ultra', 'canon_r6'). add_sensor_grain: If True, injects luminance-weighted CMOS sensor noise. grain_intensity: Noise intensity (1.0 to 2.5, default 1.4). micro_resample: If True, resamples by 0.3% with Lanczos to break frequency watermarks. simulate_lens: If True, applies optical point-spread function simulation. quality: JPEG compression quality (default 95). Returns: Detailed status of all applied anti-detection layers and output path. |
| inject_camera_profileB | Injects realistic camera EXIF (iPhone, Sony, Canon, Samsung) into a clean JPEG. Args: image_path: Path to the JPEG image file. profile_name: Camera profile id ('iphone_15_pro', 'sony_a7iv', 'samsung_s24_ultra', 'canon_r6'). output_path: Optional destination file path. Returns: Confirmation with injected hardware parameters. |
| get_camera_profilesA | Returns available camera profiles and their specifications. |
| batch_sanitize_directoryB | Sanitizes all images in a target directory with anti-AI detection processing. Args: directory_path: Directory containing images to process. output_directory: Optional folder to save sanitized images. camera_profile: Camera profile to inject ('iphone_15_pro', etc.). grain_intensity: Sensor noise level (default 1.4). Returns: Summary of processed images and outcomes. |
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 6 tools
Most tools have distinct purposes—strip, sanitize, inspect, batch, profile list/inject—but strip_metadata_only and anti_ai_sanitize overlap in metadata removal, and inject_camera_profile vs anti_ai_sanitize could be confused for camera injection. Descriptions help clarify, so only minor ambiguity.
Names are readable but inconsistent in structure: strip_metadata_only, get_camera_profiles, inspect_image_metadata, and inject_camera_profile follow verb_noun, while anti_ai_sanitize and batch_sanitize_directory deviate (adjective_noun_verb or adverb_verb_noun). This mixing makes the naming pattern less predictable.
Six tools is well-scoped for an image metadata cleaner/anti-AI sanitizer. Each tool serves a clear need: single-file strip, full sanitize, batch processing, inspection, and camera profile retrieval/injection. No redundant or unnecessary tools.
The surface covers core workflows: inspect, strip, sanitize, inject, and batch sanitize. Minor gaps include no batch inspect or batch strip-only operation, and no way to selectively remove only C2PA while keeping EXIF, but these are workarounds via existing tools.