Hangulport

Name: Hangulport
Author: CloudCorpRecords

by CloudCorpRecordsversion 0.1.0i★ –iRuns on your computer

Registry nameio.github.CloudCorpRecords/hangulport

Install

Overview

Description from the maker (original English)

Korean NLP via Bareun: morphology, dictionary search, tokenize, and grammar correction.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "hangulport": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/hangulport",
        "mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add hangulport -- npx -y @reneturcios/hangulport mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "hangulport": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/hangulport",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "hangulport": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/hangulport",
        "mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account CloudCorpRecords, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7250 servers in this category
Published to the registry more recently than 88% of the other 7250 servers in this category
Basic checks equal to or better than 100% of the other 7250 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Hangulport safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 4 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js, Docker on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

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Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

hangulport

hangulport is a client for the hosted Bareun Korean NLP service. It exposes morphological analysis with part-of-speech tagging, the raw morphological model output, Urimalsaem dictionary search by jamo slot pattern, sentence tokenization, spelling and spacing correction, and the service's part-of-speech tag list. One binary serves a command-line interface and a stdio MCP server; both forward every call to the hosted endpoint.

An API key is required. Set BAREUN_API_KEY to your Bareun key; it is sent to the endpoint as the api-key header and nowhere else. Calls go to https://api.bareun.ai/mcp unless BAREUN_MCP_URL overrides the endpoint. When the key is missing, calls fail with an error naming BAREUN_API_KEY — no result is invented locally. The 47 POS tags behind list_pos_tags are served by the upstream; they are not hardcoded here.

Install

npx @reneturcios/hangulport tokenize "안녕하세요"

Or run the container image:

docker run -i ghcr.io/cloudcorprecords/hangulport

The container defaults to the MCP server (see below). Pass CLI arguments to use it as a CLI instead. Both forms need BAREUN_API_KEY in the environment (for Docker, add -e BAREUN_API_KEY=...).

CLI

hangulport analyze_syntax "안녕하세요" --auto-spacing --encoding utf8 --format compact

hangulport analyze_syntax_raw "안녕하세요" --with-sense hangulport search_dict "ㄱㅏ*" --anchor prefix --limit 5 --with-definition hangulport tokenize "문장을 나눕니다" --auto-spacing hangulport correct_grammar "띄어쓰기연습" --enable-sentence-check hangulport list_pos_tags

hangulport --version

Each subcommand is named after the MCP tool it calls. The first argument is the required text (or dictionary pattern); the remaining flags map one-to-one onto the tool's optional inputs. Boolean flags take no value: passing the flag sets it true, and omitting it forwards nothing — this client injects no defaults of its own. --custom-dict-names takes a comma-separated list. Commands print the upstream result text. Exit codes: 0 on success, 1 when a call fails (including a missing key or an upstream error), 2 for usage errors.

MCP server

One bin serves both faces. The mcp subcommand starts a stdio MCP server:

npx -y @reneturcios/hangulport mcp

MCP client configuration:

"mcpServers": { "hangulport": { "command": "npx", "args": ["-y", "@reneturcios/hangulport", "mcp"], "env": { "BAREUN_API_KEY": "your-key" } } } }

To point the server at a different Bareun-compatible host, add BAREUN_MCP_URL to the client's env for this server.

Tools

Tool	Input	What it returns
`analyze_syntax`	`text` (required); optional `auto_split_sentence`, `auto_spacing`, `auto_jointing`, `custom_dict_names`, `encoding` (`utf32`/`utf16`/`utf8`), `format` (`full`/`compact`), `with_sense`	Morphological analysis with POS tagging.
`analyze_syntax_raw`	`text` (required); optional `auto_split_sentence`, `encoding`, `format`, `with_sense`	Raw morphological model output, no post-processing.
`search_dict`	`pattern` (required); optional `anchor` (`word`/`prefix`/`suffix`/`contains`), `pos`, `std_only`, `with_definition`, `limit`, `count_only`	Urimalsaem dictionary matches for a jamo slot pattern.
`tokenize`	`text` (required); optional `auto_spacing`, `encoding`	The sentence split into word units.
`correct_grammar`	`text` (required); optional `custom_dict_names` and nine boolean correction options (`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`)	Spelling/spacing correction blocks.
`list_pos_tags`	(none)	The 47 Bareun POS tags, as served upstream.

Development

npm install

npm run build # tsc -> dist/ npm test # node test runner over test/*.test.ts, no network (fake fetch fixtures) npm run dev # run the CLI from source via tsx

License

MIT — see LICENSE.

Hangulport

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

hangulport

Install

CLI

MCP server

Tools

Development

License