World Monitor
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.
Beschreibung vom Entwickler (englisches Original)
Korean NLP MCP server: morphological analysis, tokenization, spell & grammar checking (Bareun)
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
AuthorizationAls geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Diese Adresse braucht einen Schlüssel in einem Header der Anfrage, und das Menü zum Hinzufügen von Connectors kann ihn nicht setzen. Nutze stattdessen Claude Code, Cursor oder VS Code.
Führe das in deinem Terminal aus
claude mcp add --transport http bareun https://api.bareun.ai/mcp --header 'Authorization: your-value'Trag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"bareun": {
"url": "https://api.bareun.ai/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"bareun": {
"type": "http",
"url": "https://api.bareun.ai/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Diese Adresse braucht einen Schlüssel in einem Header der Anfrage, und das Menü zum Hinzufügen von Connectors kann ihn nicht setzen. Nutze stattdessen Claude Code, Cursor oder VS Code.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Authorization geheim erforderlich HTTP headerDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Basierend darauf, wie sich dieser Server verbindet, und auf der eigenen Doku jeder App, geprüft am 10. Nov. 2026.
Verbinden sich über das Internet in
ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast
Tool-Namen und -Beschreibungen genau so, wie der Server sie am 10. Nov. 2026 gemeldet hat. Geschrieben hat sie der Entwickler, nicht wir; wir zeigen sie als reinen Text.
analyze_syntax한국어 문장의 형태소 분석을 수행합니다. 문장을 어절·형태소로 나누고 품사를 부착합니다. format=compact 면 '표층형/품사' 요약 문자열을, full 이면 전체 구조 JSON 을 돌려줍니다. with_sense=true 를 주면 동형이의어(같은 표기, 다른 뜻: 배[腹]/배[船]/배[梨])의 의미까지 구분해 어깨번호·뜻풀이를 함께 돌려줍니다(베타).
analyze_syntax_raw후처리 없는 순수 형태소 분석을 수행합니다. 분절·품사 태깅 모델의 추론 결과를 그대로 반환하며 복합명사·복합동사 분해, 자동 띄어쓰기·붙여쓰기, 사용자 사전을 적용하지 않습니다. 모델 성능 평가나 말뭉치 재태깅처럼 후처리가 섞이지 않은 출력이 필요할 때만 쓰고, 일반적인 분석에는 analyze_syntax 를 쓰세요. with_sense=true 면 동형이의어 의미 구분(WSD, 베타) 결과도 후처리 없이 함께 돌려줍니다.
correct_grammar한국어 문장의 맞춤법·띄어쓰기를 교정합니다. 교정된 문장과 교정 블록(원문/교정문) 목록을 돌려줍니다. 원문을 다시 쓰지 않고 어긋난 자리만 고치므로 글의 문체·말투가 그대로 남습니다. 고친 자리마다 근거가 되는 한글맞춤법 조항(예: 제1장 총칙 제2항)과 설명·예시가 함께 실려 오므로, 교열 근거를 대야 하는 일에 적합합니다. 띄어쓰기가 전혀 없는 음성 인식 결과·자동 자막 원고도 복원하고 문장 경계를 찾아 문장 부호를 넣습니다.
list_pos_tags바른 형태소 분석이 사용하는 47개 품사 태그 목록(코드·이름·대분류·소분류·enum)을 JSON 으로 돌려줍니다. analyze_syntax 결과의 품사 코드(NNG, JKS 등)를 해석할 때 참고하세요.
search_dict우리말샘 사전을 자소(음소) 단위 슬롯 패턴으로 검색합니다. 완성형으로 표현할 수 없는 조건 — 초성·중성·종성 각각에 대한 조건('받침이 ㅎ인 용언', '중성이 ㅚ이고 받침 없는 1음절 어간') — 을 걸 수 있고, anchor=suffix 로 '-아지'·'-둥이'처럼 끝소리 검색도 됩니다. 각운(라임) 찾기, 초성 퀴즈·끝말잇기, 불규칙 활용 후보 수집처럼 글자를 자소로 쪼개야 풀리는 일에 씁니다. 색인 없이 사전 전체(약 100만 항목)를 훑으므로 넓은 패턴은 count_only 로 규모부터
tokenize한국어 문장을 어절(토큰) 단위로 분리합니다. 품사 정보 없이 어절 경계만 필요할 때 쓰고, 형태소·품사가 필요하면 analyze_syntax 를 쓰세요. auto_spacing=true 를 주면 띄어쓰기가 어긋난 문장도 바로잡아 나눕니다.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 11. Nov. 2026
Der Registry-Name wurde über die Domain bareun.ai bestätigt (die Registry prüft, wem die Domain gehört)
Code zuletzt geändert: vor 3 Monaten
Dieses Repo haben wir noch nicht von GitHub gelesen
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Wir haben 6 Tool-Beschreibungen gelesen und keine versteckten Anweisungen an die KI gefunden
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 4 von 4 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Das musst du eintragen: Authorization
Er läuft in der Cloud des Entwicklers. Du verbindest dich übers Internet, ohne etwas zu installieren, aber was du sendest, läuft über die Server des Entwicklers.
Das GitHub-Repo wurde zuletzt vor 3 Monaten geändert, und die neueste Version (3.0.0) kam vor 5 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.
In derselben Kategorie: World Monitor, Claude Flow, Tldraw
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:↓ Downloads pro Wochei★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.
AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
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바른(Bareun) is a Korean natural-language platform. This is its **MCP (Model
Context Protocol)** server — it lets any MCP-compatible AI tool (Claude, Cursor,
VS Code, Claude Desktop, …) perform Korean morphological analysis and
spell/grammar correction by calling Bareun as a tool.
Large language models still miss the subtle spacing, particle agreement, and confusable-word rules of Korean. Plug Bareun in as an MCP tool and your agent can hand off analysis and proofreading to a dedicated Korean engine, then use the result to produce more accurate Korean output.
https://api.bareun.ai/mcpapi-key header or Authorization: Bearer )The
/mcpendpoint is available on the spell-checker–included build of Bareun
(the morphological-analysis-only build does not expose
/mcp). The same endpoint
works on self-hosted/on-prem installs — just swap the host.
Spelling & spacing — `correct_grammar` (real output from https://api.bareun.ai/mcp):
| In | 회의결과를 정리해서 내일까지 보내주시기 바람니다. |
| Out | 회의 결과를 정리해서 내일까지 보내 주시기 바랍니다. |
Every fix comes back as a block, so an agent can explain the edit instead of silently rewriting the sentence:
| Original | Corrected | Category | Rule |
|---|---|---|---|
| 회의결과를 | 회의 결과를 | SPACING | compound noun spacing |
| 보내주시기 | 보내 주시기 | SPACING | auxiliary-verb spacing |
| 바람니다. | 바랍니다. | TYPO | misspelling |
Morphological analysis — `analyze_syntax` (format: compact):
| In | 나는 학교에 간다. |
| Out | 나/NP 는/JX 학교/NNG 에/JKB 가/VV ㄴ다/EF ./SF |
Homograph senses — `analyze_syntax` with `with_sense: true` (_beta_): 배 in 배가 아프다 comes back with senseNo: 1 and its dictionary definition — 사람이나 동물의 몸에서 … 가슴과 엉덩이 사이의 부위 (*belly*, probability 0.87), plus the Urimalsaem entry id — so the agent knows which 배 it is reading.
| Tool | What it does | Key inputs | |||
|---|---|---|---|---|---|
analyze_syntax | Splits a sentence into words/morphemes and tags parts of speech (morphological analysis). | text (required), auto_split_sentence, auto_spacing, auto_jointing, custom_dict_names, encoding, format (full\ | compact), with_sense | ||
analyze_syntax_raw | Same analysis without post-processing (no compound-noun/verb splitting, no auto spacing, no custom dictionaries) — the raw model output. | text (required), auto_split_sentence, encoding, format, with_sense | |||
search_dict | Searches the Urimalsaem Korean dictionary (~1.1M entries) by jamo (phoneme-level) slot patterns — conditions like "verbs whose stem ends in the ㅎ coda" or "words ending in -아지" that cannot be expressed with composed Hangul syllables. | pattern (required), anchor (word\ | prefix\ | suffix\ | contains), pos, std_only, with_definition, limit, count_only |
tokenize | Splits a sentence into word (token) units. | text (required), auto_spacing, encoding | |||
correct_grammar | Corrects spelling/spacing and returns correction blocks. | text (required), custom_dict_names, + 9 boolean correction options | |||
list_pos_tags | Returns the 47 part-of-speech tags Bareun uses (code · name · class). | _(none)_ |
`correct_grammar` options (all boolean, default off): treat_as_title, disable_split_sentence, disable_caret_spacing, disable_vx_spacing, enable_limited_punctuation, disable_confusion, enable_cleanup_whitespace, disable_typo_correction, enable_sentence_check.
`encoding` controls the unit for morpheme offsets: utf32 (default, code points — matches Python), utf16 (JS/Java), utf8 (bytes — Go/C++).
`with_sense` — homograph sense disambiguation (WSD, _beta_). Korean writes many unrelated words identically: 배 can be *belly*, *ship*, or *pear*. Set with_sense: true on analyze_syntax/analyze_syntax_raw and each content morpheme carries a sense object — the dictionary sense number, its Korean definition, the Urimalsaem entry id, and the probability of the chosen sense among that word's candidate senses. It is off by default (one extra model pass; responses are byte-identical to before when omitted), and format=compact renders it inline as 배__002/NNG. This feature is in beta and ships officially with Bareun 3.1.0.
| Resource URI | Contents | Auth |
|---|---|---|
bareun://pos-tags | The 47 POS tags (code · name · class) — same data as list_pos_tags | API key |
bareun://server-info | Server metadata — name · version · build · active tools/resources | API key |
bareun://custom-dicts | Names of custom-dictionary domains registered for the key | valid API key |
Tip — register globally. Most tools default to *project* scope (the server is
only available in one project). To use Bareun across all your projects, register
it at global / user scope as shown below.
# -s user → global: available in every project
claude mcp add -s user --transport http bareun https://api.bareun.ai/mcp \ --header "api-key: YOUR_API_KEY"
Omit -s user for project-local scope. Check with claude mcp get bareun.
Global: ~/.cursor/mcp.json · Project: /.cursor/mcp.json
{
"mcpServers": { "bareun": { "url": "https://api.bareun.ai/mcp", "headers": { "api-key": "YOUR_API_KEY" } } } }
Global: run MCP: Open User Configuration · Project: /.vscode/mcp.json
{
"servers": { "bareun": { "type": "http", "url": "https://api.bareun.ai/mcp", "headers": { "api-key": "YOUR_API_KEY" } } } }
claude_desktop_config.jsonClaude Desktop bridges header-authenticated remote servers via mcp-remote (Node.js required):
{
"mcpServers": { "bareun": { "command": "npx", "args": [ "-y", "mcp-remote", "https://api.bareun.ai/mcp", "--header", "api-key: YOUR_API_KEY" ] } } }
cline_mcp_settings.jsonOpen MCP Servers → Configure MCP Servers in Cline, then add:
{
"mcpServers": { "bareun": { "type": "streamableHttp", "url": "https://api.bareun.ai/mcp", "headers": { "api-key": "YOUR_API_KEY" }, "disabled": false, "autoApprove": [] } } }
All five tools are read-only (readOnlyHint), so listing them in autoApprove is safe if you would rather not confirm every call.
ChatGPT talks to Streamable HTTP servers directly — no directory review needed. Turn on Developer mode (Settings → Apps & Connectors → Advanced), then Create a connector:
https://api.bareun.ai/mcpapi-key header works just as well.)Menu wording and plan availability shift between ChatGPT releases — Developer mode is an account-level toggle, and on Business/Enterprise a workspace owner enables it first.
npx @modelcontextprotocol/inspector
Set Transport to Streamable HTTP, URL to https://api.bareun.ai/mcp, and add header api-key: YOUR_API_KEY.
// tools/call → analyze_syntax (format: compact)
{ "text": "나는 학교에 간다.", "format": "compact" } // → "나/NP 는/JX 학교/NNG 에/JKB 가/VV ㄴ다/EF ./SF"
The contents of this repository (documentation, registry manifests, examples) are released under the MIT License. The Bareun engine itself is a proprietary service operated by Baikal AI; access is governed by the bareun.ai terms of service.