MCP server that loads Pinterest board images via RSS and analyzes them to extract design tokens, style guidance, and visual foundations for Claude
Single tool 'get_board_style' has a detailed description (German, ~450 chars) but critical schema and parameter documentation gaps. Input schema visible with 'board_url' (string) and 'max_images' (integer), but lacks type constraints, ranges, enums, and error handling guidance. Description is verbose and mixes implementation details with usage intent. No output schema documented. No parameter descriptions visible in the schema itself, only in the tool description. The tool name is acceptable (verb_noun), but the overall definition lacks the rigor expected for production use.
Ladet die letzten <=25 Pins eines OEFFENTLICHEN Boards via RSS und gibt sie INLINE als Bild-Content-Bloecke (base64) + eine Analyse-Anweisung zurueck. Dadurch "sieht" Claude die Bilder direkt -> funktioniert in Claude Code UND Claude Desktop (kein Read-Tool noetig).
No output schema documented. LLMs cannot plan downstream operations or extract structured data from the response.
Parameter 'max_images' lacks constraints: no minimum, maximum, or default documented. Description says 'default 25, max 25' but schema has no defaults or bounds.
Parameter descriptions missing from JSON Schema. 'board_url' and 'max_images' have no 'description' fields in the schema object, only in the tool description text.
No error handling guidance. Tool description does not explain what happens on invalid URLs, network failures, private boards, or rate limits. LLM has no recovery path.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 49 | <=2025-11-25 | v2 |
Tool description mixes implementation details (RSS, base64, Pillow, uv, extract_facts.py) with user-facing intent. Verbose and German-language; unclear when/why to call this tool vs alternatives.