Bareun (바른) — Korean NLP & Spell Checking
Bareun (바른) is a Korean natural-language engine. This MCP server lets any MCP-compatible client hand Korean text to a dedicated Korean engine instead of guessing: analyze_syntax (morphological analysis with 47 POS tags and beta homograph sense disambiguation), analyze_syntax_raw (raw model output), tokenize, correct_grammar (spelling and spacing correction), and list_pos_tags. Hosted at https://ap
README
Bareun MCP Server — Korean NLP & Spell/Grammar Checking
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.
- Hosted endpoint:
https://api.bareun.ai/mcp - Transport: Streamable HTTP (JSON-RPC 2.0) — no SSE, no extra port, no install
- Auth: API key (
api-keyheader orAuthorization: Bearer <key>) - Get an API key: https://bareun.ai
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.
What it looks like
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.
Tools
| 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.
Resources
| 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 |
Quick start
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.
Claude Code
# -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.
Cursor
Global: ~/.cursor/mcp.json · Project: <project>/.cursor/mcp.json
{
"mcpServers": {
"bareun": {
"url": "https://api.bareun.ai/mcp",
"headers": { "api-key": "YOUR_API_KEY" }
}
}
}
VS Code
Global: run MCP: Open User Configuration · Project: <project>/.vscode/mcp.json
{
"servers": {
"bareun": {
"type": "http",
"url": "https://api.bareun.ai/mcp",
"headers": { "api-key": "YOUR_API_KEY" }
}
}
}
Claude Desktop — claude_desktop_config.json
Claude 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 — cline_mcp_settings.json
Open 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 — Developer Mode
ChatGPT talks to Streamable HTTP servers directly — no directory review needed. Turn on Developer mode (Settings → Apps & Connectors → Advanced), then Create a connector:
- URL:
https://api.bareun.ai/mcp - Authentication: OAuth — Bareun runs its own OAuth 2.1 (PKCE) endpoint, so
ChatGPT opens a login page where you paste your Bareun API key. (ChatGPT's connector
dialog offers OAuth or no-auth; if your build also lets you set request headers, an
api-keyheader 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.
Test with MCP Inspector
npx @modelcontextprotocol/inspector
Set Transport to Streamable HTTP, URL to https://api.bareun.ai/mcp, and
add header api-key: YOUR_API_KEY.
Example
// 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"
Links
- Service: https://bareun.ai
- Docs: https://bareun.ai/docs
- MCP guide: https://bareun.ai/docs/howtouse/mcp
- API keys & usage: https://bareun.ai/docs/howtouse/cloud-api
License
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.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。