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Dict

作者:azerbaijan-mcp版本 0.1.2i★ –i在你的电脑上运行
注册名称io.github.azerbaijan-mcp/dict

安装

概览

作者提供的说明(英文原文)

Look up words in the Azerbaijani explanatory dictionary; downloads its database once (local only).

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 搜索与 AI 记忆

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "dict": {
      "command": "uvx",
      "args": [
        "azerbaijan-mcp-dict"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add dict -- uvx azerbaijan-mcp-dict

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "dict": {
      "command": "uvx",
      "args": [
        "azerbaijan-mcp-dict"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "dict": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "azerbaijan-mcp-dict"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月9日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 azerbaijan-mcp 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“搜索与 AI 记忆”中的其他服务器比较i

  • 星标数多于此分类中其他 5747 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 5747 个服务器的 88% 更新
  • 基础检查结果等于或优于此分类中其他 5747 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Dict 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.1.2)于5天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它?

同一分类中有:Context7, Codebase Memory, Exa

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Context7

Up-to-date docs for AI agents

作者:upstash广泛使用↓ 97.3万/周★ 6.4万前天更新

电脑或云端

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

作者:DeusData广泛使用↓ 1.8万/周★ 4.8万22天前更新

在你的电脑上运行

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

作者:exa-labs广泛使用★ 52132个月前更新

在云端运行✓ exa.ai

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

azerbaijan-mcp-dict

Local-only MCP server for the explanatory dictionary of the Azerbaijani language, *Azərbaycan dilinin izahlı lüğəti* (four volumes, about 45,000 entries). It looks words up, finds entries by what they say and walks the dictionary in print order, with the volume, page and column of every entry.

On first use the server downloads the dictionary's database once, 5.6 MB, from this project's release page and keeps it in your cache folder with a search index built from it. The dictionary is a copyrighted print work and the project has no licence for it: read *Data source and terms* below. Set DICT_DB to use a database of your own instead. The server runs on your computer and is never offered as a hosted service.

Tools

ToolWhat it does
define(word, max_chars?)The entries of a headword, in print order, with their meanings, etymology note (origin), place in the volumes and the headwords their bax pointers lead to. Homonyms are separate entries (ÇAY¹, ÇAY²). Entries are cut at max_chars (3,000 by default, up to 50,000). A miss lists headwords to try.
search(query, exact?, limit?, offset?)The entries whose text has all the words, the headword the query spells first. Use it to find a word by its meaning (su qabı). limit is 1-50 (default 10) and next_offset pages on.
browse(word?, entry_id?, before?, after?)The entries around a headword in print order, like turning the pages: before and after are 0-50 (3 and 7 by default). next_id and previous_id go on from either end.
read_entry(entry_id, offset?, max_chars?)An entry from a character offset, to read what define or search cut short. A few entries run to tens of thousands of characters.

A typical question, "what is the word for a vessel for water?", takes search("su qabı"), then define of the headword it finds. "What comes after *kitab* in the dictionary?" is browse("kitab").

Things worth knowing:

  • Base forms. The dictionary lists headwords, not inflected forms: look up kitab, not kitabları. define then answers match: none with suggestions (the stem, headwords that begin with the word, near misses) and a note.
  • What `define` forgives. A headword typed as printed (AB(B)ASI, ÇAY², AB-HAVA, ABÜHAVA) or with the number a pointer gives it (çay2); other dashes, curly quotes and invisible characters. Case: I and İ are different letters and are lower-cased as Azerbaijani does. Accents and hyphens, when no headword is spelled as given: seher finds şəhər and səhər (match: accent_free); a space stands for a hyphen (ata baba). A variant is found under each spelling: AB(B)ASI as abası and abbası, AB-HAVA,ABÜHAVA as two words. An exact spelling wins over the same word without accents (el and əl are different words).
  • `bax` pointers. An entry that only says bax X (see X) comes with X's entry in followed, two steps at most. Other pointers inside an entry are listed in see, with the entries they lead to. A pointer to a numbered sense (bax dərd 3-cü mənada) leads to the headword: read its text for the sense.
  • Searching. All words must be in the entry; there are no operators such as OR, and at most twelve words are used. Azerbaijani adds endings, so a word of four letters or more is matched by its first five letters (içmək finds içir and içən); exact=true matches whole words. Accents must be right here, unlike in define.
  • Citations. Every entry has volume, pdf_page and column. The page is the page of the volume's PDF, which can differ from the printed page number.
  • The text is a machine extraction of the PDF text layer and may contain errors. Lines are joined; a hyphen at the end of a line is dropped unless the dictionary spells the compound with a hyphen more often than without (ata-baba), or the word is a doubled one (aşkar-aşkar), a number with its ending (1931-ci) or starts with qeyri-; a compound that occurs only once, broken at its hyphen, loses the hyphen. The letter-spaced italic b a x of the PDF is read as bax. Cite the printed dictionary, not this server.
  • Etymology. origin is the note in square brackets after the part of speech (ər., fars., fr., əsli lat.); about 11,000 entries have one.
  • The first call downloads the database and builds the index, which takes a few seconds: about 10 seconds and 30 MB of index for the whole dictionary. Both are kept in the cache folder (%LOCALAPPDATA%\azerbaijan-mcp\dict on Windows, ~/Library/Caches/azerbaijan-mcp/dict on macOS, ~/.cache/azerbaijan-mcp/dict elsewhere) and reused until the database file changes. Each database gets its own index file, so several can share the folder. A database you name is opened read-only and never written. The cache can be deleted at any time: the next call fetches and builds again. A file cut short, because the process was killed while it was being copied into place, is noticed and fetched or built again.
  • Not covered: inflected forms (no morphology), and the dictionary's other editions and sibling dictionaries.

Install

Add to your MCP client configuration (requires uv):

{

"mcpServers": { "dict": { "command": "uvx", "args": ["azerbaijan-mcp-dict"] } } }

In Claude Code: claude mcp add dict -- uvx azerbaijan-mcp-dict.

Three optional settings go in the client's env:

VariableDefaultMeaning
DICT_DBnonePath of a dictionary database of your own. The published one is then not downloaded.
DICT_DATA_URLthe release page of this repositoryA mirror of the published database, https only (http for this computer). Its SHA-256 is still checked.
DICT_CACHE_DIRthe cache folder aboveWhere the database and the index are kept. A folder where the system refuses renames works too, for example %LOCALAPPDATA% for a server the Claude desktop app starts on Windows (WinError 17): the files are copied into place instead.

The database

The published database is the file dict-1.sqlite.gz of the release dict-data-1: 45,353 entries, 5,657,352 bytes, SHA-256 44515ffca32d7cefc9f659bbe1ecefa82dc6908f17b5d434daffd1f921162022, which the package pins, so a file that differs is never used. python -m azerbaijan_mcp_dict.asset source.sqlite out.sqlite.gz packs a database that way and prints the numbers to pin.

A database of your own needs one table, entries, and the server reads only the columns below. A metadata table is optional.

CREATE TABLE entries (

id INTEGER PRIMARY KEY, -- print order volume INTEGER NOT NULL, -- 1 to 4 headword TEXT NOT NULL, -- as printed: ÇAY, AB(B)ASI, AB-HAVA,ABÜHAVA homonym_index INTEGER, -- 1, 2, ... for homonyms, else NULL entry_text TEXT NOT NULL, -- what follows the headword, lines as the PDF breaks them start_page INTEGER NOT NULL, -- PDF page of the volume the entry starts on end_page INTEGER NOT NULL, start_column INTEGER NOT NULL -- 1 or 2 ); CREATE TABLE metadata (key TEXT PRIMARY KEY, value TEXT NOT NULL);

metadata keys that are used: database_title, which names the source in every answer, and entry_count, which is checked against the table so that a truncated file is refused. Other columns and tables are ignored. The database the published one was made from has a full-text index of its own; the server does not use it, because it misses every word that starts a sentence with a capital İ (iki finds 1,324 of the 1,656 entries that have it). A script that rebuilds the database from the PDFs is tracked in MCP-31.

Data source and terms

The only request the server makes is the one download of the database, from github.com, once for each cache folder. Answers to the checklist in the repository's data policy, read on 2026-11-03:

  • Publisher: bibliographies list the dictionary as published by Şərq-Qərb, Baku, 2006 (compiled by Ə. Orucov and others, edited by A. Axundov). No official online edition was found; azleks.az offers an electronic version behind a registration whose terms are unclear, and unofficial scans circulate.
  • Terms and licence: none found, so the text is treated as all rights reserved. The project's owner decided on 2026-11-03 to publish the extracted database as a release asset of this repository all the same, without asking the publisher. That departs from the data policy's rule that terms win and carries the risk of a complaint. The text is in that release asset only, never in the package, the repository or the tests. If the publisher, the authors or their heirs object, the asset is deleted promptly.
  • robots.txt, rate limit and cache: not applicable to a release file. The download sends the User-Agent azerbaijan-mcp-dict/ (+ ), makes one request, retries once for a network error or a server error, stops on HTTP 403 and 429, refuses more than 100 MB and uses nothing whose SHA-256 differs from the pinned one. It is kept for good in the cache folder. The tests run with outside network access blocked.
  • Attribution: every answer has source (the database's title) and an attribution that says the text is an unofficial machine extraction, and every entry has its volume, PDF page and column.
  • Personal data: none. The entries quote published literature with the author's name, as the dictionary does; nothing about private people is returned or stored.
  • Publisher contacted: no (MCP-32).
  • Decision: go, local stdio only, with the database published as a release asset (MCP-34).

tests/ builds an invented dictionary in the layout of the real one; no line of the real dictionary is in this repository. To run the contract tests against your own database, and to check the published one:

DICT_DB=/path/to/azerbaycan_lugeti_1-4.sqlite uv run pytest -m live packages/dict

Unofficial project, not affiliated with or endorsed by the publisher or the institute that compiled the dictionary.

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