Naver Search MCP server

Provides access to Naver's search APIs across multiple categories including blogs, news, books, images, and shopping items with structured responses optimized for Korean-language search capabilities.
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Setup instructions
Provider
Anthony Kim
Release date
Apr 30, 2025
Language
Python
Stats
3 stars

The Naver Search MCP server provides a convenient interface to Naver's search capabilities for AI assistants, allowing them to search for blogs, news, books, images, shopping items, and more through the Model Context Protocol (MCP).

Installation

Prerequisites

Standard Installation

  1. Clone the repository:

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

    curl -LsSf https://astral.sh/uv/install.sh | sh
    
  3. Create a virtual environment and install dependencies:

    uv venv -p 3.12
    source .venv/bin/activate
    pip install -r requirements.txt
    
  4. Configure your Naver API credentials:

    cp env.example .env
    

    Edit the .env file to add your API credentials:

    NAVER_CLIENT_ID=your_client_id_here
    NAVER_CLIENT_SECRET=your_client_secret_here
    

Docker Installation

  1. Build the Docker image:

    docker build -t py-mcp-naver-search .
    
  2. Run the container:

    docker run py-mcp-naver-search
    

Running the Server

Local Execution

mcp run server.py

To run with the MCP Inspector for debugging:

mcp dev server.py

Client Configuration

Claude Desktop App

Automatic Installation via Smithery

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

Manual Installation

Edit ~/Library/Application Support/Claude/claude_desktop_config.json and add 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

Edit ~/.cursor/mcp.json and add to the mcpServers object:

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

Docker Configuration

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

Usage Examples

Basic Search Commands

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

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

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

# Check if content is adult-oriented
uv run client.py adult "your query"

# Correct keyboard input errors
uv run client.py errata "spdlqj"

Supported Search Categories

The server provides access to these Naver search types:

  • 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
  • image - Images
  • webkr - Web documents

Search Parameters

Common Parameters

Most search functions accept these parameters:

  • query: The search term (required)
  • display: Number of results to return (default: 10)
  • page: Page number for pagination (default: 1)
  • sort: Sorting method (default: "sim" for similarity)

Special Parameters

  • For image searches: filter parameter to filter by size (options: "all", "large", "medium", "small")
  • For local searches: Default sort is "random"

Response Format

All search tools return structured text responses optimized for AI assistants:

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
...

How to install this MCP server

For Claude Code

To add this MCP server to Claude Code, run this command in your terminal:

claude mcp add-json "Naver-Search" '{"command":"/path/to/bin/uv","args":["--directory","/path/to/py-mcp-naver-search","run","server.py"]}'

See the official Claude Code MCP documentation for more details.

For Cursor

There are two ways to add an MCP server to Cursor. The most common way is to add the server globally in the ~/.cursor/mcp.json file so that it is available in all of your projects.

If you only need the server in a single project, you can add it to the project instead by creating or adding it to the .cursor/mcp.json file.

Adding an MCP server to Cursor globally

To add a global MCP server go to Cursor Settings > Tools & Integrations and click "New MCP Server".

When you click that button the ~/.cursor/mcp.json file will be opened and you can add your server like this:

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

Adding an MCP server to a project

To add an MCP server to a project you can create a new .cursor/mcp.json file or add it to the existing one. This will look exactly the same as the global MCP server example above.

How to use the MCP server

Once the server is installed, you might need to head back to Settings > MCP and click the refresh button.

The Cursor agent will then be able to see the available tools the added MCP server has available and will call them when it needs to.

You can also explicitly ask the agent to use the tool by mentioning the tool name and describing what the function does.

For Claude Desktop

To add this MCP server to Claude Desktop:

1. Find your configuration file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json

2. Add this to your configuration file:

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

3. Restart Claude Desktop for the changes to take effect

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