should-i-use

Token-efficient library docs MCP server. Honest library recommendations for coding agents: what to install, what to skip, and how to use it, in 25-360 tokens per answer (hard-clamped at 500). 992 npm + PyPI libraries indexed, docs-grounded and validator-gated, top-50 install-verified. Audits your dependencies for unmaintained packages. A Context7 alternative that answers the question instead of dumping documentation — 4.8x fewer tokens in a 10-round random-sample benchmark.

该来源不提供完整文件导出（国内平台多为平台内托管），仅存元数据与原链

模型生成摘要（rules/v1 · 2026-09-27 17:03）：Token-efficient library docs MCP server
这是模型对公开材料的总结，不是官方声明，请以原链内容为准。

接入信息

传输形态: http
鉴权方式: 鉴权未知
端点: https://should-i-use--mrkeyoor.run.tools

鉴权方式未标注，请核对官方文档后再接入——不要直接使用以下片段

{
  "mcpServers": {
    "should-i-use": {
      "url": "https://should-i-use--mrkeyoor.run.tools"
    }
  }
}

能力清单

工具	说明
pick_library	Given a coding task, recommend 1-3 libraries from the should-i-use index with one-line reasoning and an honest warning about the top pick. Use before installing anything.
should_i_use	Honest verdict on a specific library: 4-axis scores with reasons, when to skip it, and maintenance signals (last push, weekly downloads).
alternatives	Curated alternatives to a library, each with a one-line "prefer it when" and a verdict if the alternative is also indexed.
how_do_i	Return the 1-2 best code snippets for a task with a library, plus the gotcha for each. Snippets are correct for the indexed version. Far cheaper in tokens than a docs dump.
audit_dependencies	Audit a project's dependencies for unmaintained packages, unstable APIs, and documented reasons to switch. Pass the contents of package.json, requirements.txt, or pyproject.toml. Returns only the dependencies worth a decision, not a report on every line. Run this before working in an unfamiliar codebase.
docs_link	Official docs URL and GitHub repo for a library, one line each. Use when the clamped answers are not enough.

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