MCP server for reading WeChat (微信) Official Account articles, with native multimodal output (images + video keyframes).
Single tool 'read_article' has a clear, detailed description (194 chars) and proper input schema with type and description. However, output schema is explicitly set to null (output_schema=None), preventing validation and documentation of the multimodal response structure. Parameter descriptions are present but minimal. No error handling guidance for LLMs (e.g., 'if fetch fails, try again' or 'check URL format'). Tool is read-only and well-scoped, but lacks the structured output documentation and error recovery patterns expected of production tools.
Read a WeChat Official Account article (mp.weixin.qq.com/s/...) and return its content as a multimodal block list: - First text block: title, account, publish time, cover URL, video count, and the full article body in Markdown. - Image blocks: the article's PNG/JPG images (GIFs filtered out, capped at 10) returned as native image content so the LLM can see them directly. - Per-video groups: a text marker `video kind=... vid=... keyframes=N` followed by N evenly-spaced keyframe images (capped at 3 videos). On failure the response is a single text block starting with "Error:".
Output schema explicitly set to null; multimodal response structure (text blocks, image blocks, video keyframes) is undocumented and unvalidated. LLMs cannot infer the response format or plan downstream processing.
Error responses are unstructured text blocks starting with 'Error:' (e.g., 'Error: fetch failed: ...'). No error classification (retryable vs. fatal), no recovery guidance, no structured error object. LLMs cannot distinguish transient failures from permanent ones.
Parameter 'url' description is minimal ('A WeChat article URL, format: https://mp.weixin.qq.com/s/xxx'). Does not explain what happens on invalid URLs, whether redirects are followed, or timeout behavior. Baseline for param descriptions is 72 chars; this is ~50 chars.
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 55 | <=2025-11-25 | v2 |
Tool description mentions 'capped at 10' images and '3 videos' but does not explain why or what happens when limits are exceeded. No mention of timeout, rate limiting, or resource constraints that affect LLM planning.
STDIO transport only. Server is not remotely accessible and cannot be used by hosted MCP clients (e.g., Claude web, Anthropic API). Limits deployment and integration scenarios.