Proofly (Deepfake Detection)
The Proofly MCP server enables AI assistants to detect deepfakes in images through integration with the Proofly API. Developed by Proofly AI, this Node.js implementation provides tools for analyzing images (via base64 or URL), checking analysis session status, and retrieving detailed face information. The server communicates via stdio using the Model Context Protocol SDK, processes images through the Proofly API (api.proofly.ai), and returns detailed analysis results including real/fake probability scores and individual model results for each detected face. It's designed to work with MCP-compatible clients like Claude Desktop, Cursor, and Cascade/Windsurf, making it valuable for users who need to verify image authenticity without leaving their conversation context.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- media
- Source
- PulseMCP
- Repository
- github.com/prooflie/mcp
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve Proofly (Deepfake Detection) from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.