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English(EN) We checked 46 popular MCP servers on Smithery: 7 in 10 tools never say when to use them

AI 工具缺乏清晰度:70% 的描述未能解释用法

对 Smithery 上 46 个热门 MCP 服务器的最新分析显示,它们的工具描述存在严重缺陷。在检查的 1,118 个工具中,约有 69% 未能明确其预期用途,45% 未描述其返回值。此外,同一服务器内的工具描述通常非常相似,以至于 AI 代理可能会混淆它们,有 15 个服务器在 90 对工具中出现了此问题。正如 PubMed 和 Gmail 的示例所示,这种缺乏清晰度可能导致 AI 代理错误地选择工具。 AI

影响 清晰的工具描述缺失阻碍了 AI 代理的功能,并增加了自动化任务出错的风险。

排序理由 对现有工具及其描述的分析。[lever_c_demoted from research: ic=1 ai=0.7]

在 dev.to — MCP tag 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

AI 工具缺乏清晰度:70% 的描述未能解释用法

本文如何被排名

Signal score
2 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
对现有工具及其描述的分析。[lever_c_demoted from research: ic=1 ai=0.7]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
product, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Same-day
Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

  1. dev.to — MCP tag TIER_1 English(EN) · Hiroki Nomura ·

    我们在 Smithery 上检查了 46 个流行的 MCP 服务器:10 个中有 7 个工具从不说明何时使用它们

    <p>We took 46 of the most-used MCP servers on Smithery and checked the descriptions of all 1,118 of their tools. <strong>769 tools (69%) never say when to use them.</strong> 507 (45%) never say in their description what they return. And 15 servers have tools whose descriptions ar…