Categories › Media & Design › Image generation & editing
Calibrated vision for AI agents: meal nutrition, personal color, styling reports. x402, no API key.
Remote server: your requests and data go to mart402.com. Claude Code: claude mcp add --transport http vision https://mart402.com/mcp/vision · Claude app: Settings → Connectors → Add custom connector.
The tools this server listed when we connected to it, in its own words.
get_catalog — Mart402 product catalog: all products, prices, payment config, error codes, rate limits. Free.get_receipt — Re-fetch a previously paid result for free by receipt id (every paid response carries receipt_id).get_sample — Free recorded sample response for a paid product (from real production runs, marked sample:true) - see the exact response shape before payinportrait_precheck — FREE analyzability check before paying for portrait_analysis: is a face detectable, is the photo quality good enough (clipping/color cast)? meal_vision — Analyze a meal photo to itemized nutrition JSON: dishes, portions, kcal, macros with per-item confidence, reference-object scale calibrationstyle_profile — Integrated styling verdict: seasonal color (measured colorimetry consensus) + face-impression zone (published geometry rules) + body frame +style_report — Client-ready deliverable: the style-profile analysis rendered as a finished PDF report in English or Japanese (palette with color names, styreport_pack — Volume pricing for style_report: one $19.90 payment returns 10 single-use credit codes ($1.99/unit vs $2.99 single, en or ja, no expiry). Trportrait_analysis — Personal color analysis from 1-3 portraits: measured pixel colorimetry (CIELAB/ITA) cross-checked against vision-model attributes, cross-phoNot tested by KitScout yet. When our harness runs it, pros, cons and the tasks we tried appear here, with the date and evidence.