Check AI Free MCP Server
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- AlicenseNot gradedqualityCmaintenanceEnables an agent to determine whether an image is AI-generated, edited, or captured by reading signed C2PA Content Credentials first and falling back to labelled pixel-level forensic heuristics (noise, ELA, spectral, colour, EXIF) only when no manifest exists. Runs fully offline with no API keys or cloud calls, and can report tampering when pixels no longer match a signed hash.MIT
- AlicenseAqualityDmaintenanceEnables reading and verifying C2PA Content Credentials from images and videos through both embedded manifests and invisible watermarks. Supports direct filesystem access, URL checking, and provides structured provenance data including creator identity, AI generation info, and content authenticity.2MIT
- AlicenseNot gradedqualityBmaintenanceEnables LLM agents to autonomously run sub-3ms multi-spectral forensic inspection of claim images to detect generative AI inpainting, deepfake tampering, duplicate reuse, and screen-recapture attacks. Exposes tools for CLAHE normalization, JPEG ghost sweeping, azimuthal Fourier harmonic probing, CMOS sensor-noise (PRNU) analysis, full claim triage, and immutable audit-ledger retrieval, returning automated approve/review/reject verdicts.1Apache 2.0
- AlicenseAqualityCmaintenanceProvides MCP-compatible AI agents with a verify_image tool to check a photo's capture time and provenance using C2PA, EXIF, XMP metadata, and pixel forensics, returning a verdict and confidence score.1128 npm2MIT
- AlicenseAqualityBmaintenanceVerifies C2PA Content Credentials for local files or URLs and returns an LLM-ready verdict on trust, AI generation, and provenance.430 npm2Apache 2.0
- AlicenseNot gradedqualityDmaintenanceEnables LLMs to analyze images, videos, audio, and text files for AI-generated content using the Reality Defender API, with support for user file uploads and direct URL analysis.1Apache 2.0
TDQS
Scored across 2 tools
detect_ai_image and inspect_c2pa_provenance both inspect image source/metadata clues, creating some conceptual overlap. However, the descriptions distinguish them: one targets AI-generation signals, the other targets C2PA/camera provenance specifically.
Both tools follow a clean snake_case verb_noun pattern (detect_ai_image, inspect_c2pa_provenance). No stylistic deviations.
Two tools is thin even for a narrowly scoped image-forensics adapter. A couple of complementary operations (e.g. raw metadata extraction) could reasonably round it out.
The surface covers AI-signal detection and provenance inspection but is explicitly read-only with acknowledged limitations (no signature verification, no pixel-model fallback). Notable capabilities in the domain are missing, though the stated scope is narrow.