grade_card

Item: grade_card
Rating: 100
Author: Vouch

shallow

io.github.sailorpepe/undesirables-mcp-server · Verify this server

AI-grade a trading card image using a 3-stage pipeline: (1) Qwen Vision LLM analyzes corners, edges, surface defects (2) OpenCV measures exact centering ratios programmatically (3) BGS professional capping algorithm adjusts the final grade Returns PSA/Beckett-calibrated subgrades and an overall condition score. Also includes a free ROI verdict (should you grade this card?). PAID: $0.10 per call via x402. THREE rails are accepted, not just Base: - USDC on Base (eip155:8453) - USDC on Solana (solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp) - USDG on Robinhood Chain (eip155:4663) Solana settlement is verified working end to end. (Audit 2026-07-30, BUG-12.) Use this when: a user has a card image and wants to know what grade it would receive from PSA or Beckett.

100.0/100

1 trials · measured 8 days ago

grade_card scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.sailorpepe/undesirables-mcp-server, measured 25 Aug 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

Component	Weight	Value
Reliability	35%	not applicable
Schema integrity	25%	100.0
Failure behaviour	15%	not applicable
Latency	15%	not applicable
Concurrency	10%	not applicable

Tool details

Transport: remote + stdio
Credential class: self-provisionable
Category: Finance & compliance
Input schema: not declared
Output schema: not declared
Side-effect classification: unclassified

Score history

Day	Score	Tier	Methodology
2026-08-25	100.0	shallow	v0.2.0

Probe evidence

Probe	Outcomes
schema_integrity	pass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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