
Glossarygen
io.github.CloudCorpRecords由 GitHub 账号 CloudCorpRecords 发布v0.1.0更新于 Nov 3, 2026
根据提供的代码和文档术语构建项目词汇表,合并并附上来源链接。
AI 翻译由 AI 模型根据下方的原文描述翻译,可能有误。
原文描述
Build a project glossary from supplied code and doc terms, merged, with source links.
概览
Glossarygen 的本地 MCP 服务;无需登录;STDIO。
暂无 AI 概览:以下信息来自注册中心条目和服务本身。
安装
在 SourceWeft 中
- 打开 控制台中的 Glossarygen,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
glossarygen
A project accumulates names faster than it accumulates
explanations for them: the same concept shows up as
user_id in the database layer, UserID in an API type,
and "user id" in the docs, and nobody can say whether
those are one term or three. glossarygen settles that
kind of question from facts you already have. You supply
term occurrences — each name exactly as you found it,
where you found it, and a definition when the docs carry
one — and glossarygen hands back a single merged
glossary: one entry per distinct term, with every source
the term was seen in and the definition the docs gave
it, if any. It writes no definitions of its own and
fetches nothing; it only normalizes and merges what you
supplied.
Normalization follows a fixed recipe, in order. First,
every run of underscores or hyphens becomes a single
space. Then camel humps are split: a space goes before an
uppercase letter that follows a lowercase letter or a
digit, and before an uppercase letter that ends an
acronym run and starts a capitalized word, so
HTTPServer becomes HTTP Server. The result is split
on whitespace and every word is lowercased; the words
joined with single spaces form the term's key. That is
why parseHTTPResponse keys as parse http response,
and why user_id and UserID land on the same key,
user id, and merge into one entry.
Each entry shows its term in display form — the key with
its first character uppercased, so parse http response
reads as Parse http response — together with the
distinct sources across all its occurrences, sorted
ascending, and how many occurrences merged into it. The
entry's definition is the first one supplied in your
order among the merged occurrences; an empty-string
definition still counts as supplied and is kept exactly
as given, and when no occurrence supplies one the
definition is null. Entries come back sorted by key,
and the counts report how many occurrences you supplied,
how many distinct terms they merged into, and how many
of those terms carry a definition versus not.
A name made only of separators, like ___, normalizes
to no words at all and is a validation error naming its
path, as are a missing or empty term list, a non-object
occurrence, a missing, empty, or non-string name or
source, and a definition that is present but not a
string. Invalid input produces no partial glossary.
Unknown extra fields are ignored.
CLI
args.json contains the full arguments object:
The glossary is printed as JSON:
Exit codes: 0 on success, 1 on a runtime error
(including an unreadable or invalid input file, or
invalid input), 2 on a usage error.
MCP server
MCP client config:
Tools
-
build_glossary— Build a project glossary from caller-supplied terms: identifier and doc names are normalized and merged, each entry carrying its sources and its supplied definition, if any.terms(array, required, at least 1 item) — the term occurrences to merge, in the caller's order; each item:name(string, required, non-empty) — term as found: an identifier or a doc phrasesource(string, required, non-empty) — where the term was found (a path or link), echoed as the entry's sourcedefinition(string, optional) — a definition found in the docs
Returns
{entries, counts}, whereentriesholds one{term, sources, occurrences, definition}per distinct normalized term, sorted by term key, andcountsis{supplied, distinct_terms, with_definition, without_definition}.
Docker
Development
License
MIT — Copyright (c) 2026 Rene Turcios
来源:README.md,提交 0e4d85d
工具
0版本历史
1- v0.1.0最新Nov 3, 2026
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