Context7
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Description from the maker (original English)
Look up words in the Azerbaijani explanatory dictionary; downloads its database once (local only).
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"dict": {
"command": "uvx",
"args": [
"azerbaijan-mcp-dict"
]
}
}
}Run this in your terminal
claude mcp add dict -- uvx azerbaijan-mcp-dictPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"dict": {
"command": "uvx",
"args": [
"azerbaijan-mcp-dict"
]
}
}
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Paste into .vscode/mcp.json in your project
{
"servers": {
"dict": {
"type": "stdio",
"command": "uvx",
"args": [
"azerbaijan-mcp-dict"
]
}
}
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We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 9, 2026
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Runs on your computer and uses local settings instead
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In the same category: Context7, Codebase Memory, Exa
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Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
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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.
| Tool | What 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:
kitab, not kitabları. define then answers match: none with suggestions (the stem, headwords that begin with the word, near misses) and a note.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 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.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.volume, pdf_page and column. The page is the page of the volume's PDF, which can differ from the printed page number.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.origin is the note in square brackets after the part of speech (ər., fars., fr., əsli lat.); about 11,000 entries have one.%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.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:
| Variable | Default | Meaning |
|---|---|---|
DICT_DB | none | Path of a dictionary database of your own. The published one is then not downloaded. |
DICT_DATA_URL | the release page of this repository | A mirror of the published database, https only (http for this computer). Its SHA-256 is still checked. |
DICT_CACHE_DIR | the cache folder above | Where 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 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.
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:
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.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.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.