Naver Search MCP Server

This MCP (Multi-platform Communication Protocol) server provides access to Naver Search APIs, allowing AI agents to search for various types of content on Naver.

Overview

Search for blogs, news, books, images, shopping items, and more
Multiple search categories with pagination support
Structured text responses optimized for LLM consumption
Check for adult content
Convert keyboard input errors (errata)

Setup

Prerequisites

Python 3.12+
Naver Developer API credentials
- You can obtain these credentials by signing up at the Naver Developers portal.
- And You can check my blog Naver Search API MCP Server, too.

Installation

Clone the repository:

git clone https://github.com/jikime/py-mcp-naver-search.git
cd py-mcp-naver-search

uv installation

curl -LsSf https://astral.sh/uv/install.sh | sh

Create a virtual environment and install dependencies:

uv venv -p 3.12
source .venv/bin/activate
pip install -r requirements.txt

Create a .env file with your Naver API credentials:

cp env.example .env
vi .env

NAVER_CLIENT_ID=your_client_id_here
NAVER_CLIENT_SECRET=your_client_secret_here

Using Docker

Build the Docker image:

docker build -t py-mcp-naver-search .

Run the container:

docker run py-mcp-naver-search

Using Local

Run the server:

mcp run server.py

Run the MCP Inspector

mcp dev server.py

Configure MCP Settings

Add the server configuration to your MCP settings file:

Claude desktop app

To install automatically via Smithery:

npx -y @smithery/cli install @jikime/py-mcp-naver-search --client claude

To install manually open ~/Library/Application Support/Claude/claude_desktop_config.json

Add this to the mcpServers object:

{
  "mcpServers": {
    "Google Toolbox": {
      "command": "/path/to/bin/uv",
      "args": [
        "--directory",
        "/path/to/py-mcp-naver-search",
        "run",
        "server.py"
      ]
    }
  }
}

Cursor IDE

open ~/.cursor/mcp.json

Add this to the mcpServers object:

{
  "mcpServers": {
    "Google Toolbox": {
      "command": "/path/to/bin/uv",
      "args": [
        "--directory",
        "/path/to/py-mcp-naver-search",
        "run",
        "server.py"
      ]
    }
  }
}

for Docker

{
  "mcpServers": {
    "Google Toolbox": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "py-mcp-naver-search"
      ]
    }
  }
}

Using the Client

The repository includes a client script for testing:

# Basic search
uv run client.py blog "Python programming" display=5 page=1

# News search with sorting
uv run client.py news "AI" display=10 page=1 sort=date

# Image search with filtering
uv run client.py image "cat" display=10 filter=large

# Check for adult content
uv run client.py adult "your query"

# Errata correction
uv run client.py errata "spdlqj"

Available Search Categories

The server supports the following search categories:

blog - Blog posts
news - News articles
book - Books
adult - Adult content check
encyc - Encyclopedia entries
cafe_article - Cafe articles
kin - Knowledge iN Q&A
local - Local business information
errata - Keyboard input error correction
shop - Shopping items
doc - Academic papers and documents
image - Images
webkr - Web documents

API Reference

Tools

Search Blog

search_blog(query: str, display: int = 10, page: int = 1, sort: str = "sim") -> str

Searches for blogs on Naver using the given keyword.

Search News

search_news(query: str, display: int = 10, page: int = 1, sort: str = "sim") -> str

Searches for news on Naver using the given keyword.

Search Book

search_book(query: str, display: int = 10, page: int = 1, sort: str = "sim") -> str

Searches for book information on Naver using the given keyword.

Check Adult Query

check_adult_query(query: str) -> str

Determines if the input query is an adult search term.

Search Encyclopedia

search_encyclopedia(query: str, display: int = 10, page: int = 1, sort: str = "sim") -> str

Searches for encyclopedia information on Naver using the given keyword.

Search Cafe Article

search_cafe_article(query: str, display: int = 10, page: int = 1, sort: str = "sim") -> str

Searches for cafe articles on Naver using the given keyword.

Search KnowledgeiN

search_kin(query: str, display: int = 10, page: int = 1, sort: str = "sim") -> str

Searches for Knowledge iN Q&A on Naver using the given keyword.

Search Local

search_local(query: str, display: int = 5, page: int = 1, sort: str = "random") -> str

Searches for local business information using the given keyword.

Correct Errata

correct_errata(query: str) -> str

Converts Korean/English keyboard input errors.

Search Shop

search_shop(query: str, display: int = 10, page: int = 1, sort: str = "sim") -> str

Searches for shopping product information on Naver using the given keyword.

Search Document

search_doc(query: str, display: int = 10, page: int = 1) -> str

Searches for academic papers, reports, etc. using the given keyword.

Search Image

search_image(query: str, display: int = 10, page: int = 1, sort: str = "sim", filter: str = "all") -> str

Searches for images using the given keyword.

Search Web Document

search_webkr(query: str, display: int = 10, page: int = 1) -> str

Searches for web documents using the given keyword.

Resources

Available Search Categories

GET naver://available-search-categories

Returns a list of Naver search categories available on this MCP server.

Response Format

All tools return responses in structured text format, optimized for LLM processing:

Naver Blog search results (total 12,345 of 1~10):

### Result 1
Title(title): Sample Blog Post
Link(link): https://blog.example.com/post1
Description(description): This is a sample blog post about...
Blogger name(bloggername): John Doe
Blogger link(bloggerlink): https://blog.example.com
Post date(postdate): 20250429

### Result 2
...

Acknowledgements

License

This project is licensed under the MIT License - see the LICENSE file for details.

This server cannot be installed

security - not tested

license - not found

quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Provides access to Naver Search APIs, allowing AI agents to search across multiple categories (blogs, news, books, images, shopping items, etc.) with structured responses optimized for LLM consumption.

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