py-mcp-naver-search

# Naver Search MCP Server [](https://smithery.ai/server/@jikime/py-mcp-naver-search)    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) ## Table of Contents - [Prerequisites](#prerequisites) - [Installation](#installation) - [Configure MCP Settings](#configure-mcp-settings) - [API Reference](#api-reference) - [Acknowledgements](#acknowledgements) - [License](#license) ## Setup ### Prerequisites - Python 3.12+ - Naver Developer API credentials - You can obtain these credentials by signing up at the [Naver Developers](https://developers.naver.com/apps/#/register) portal. - And You can check my blog [Naver Search API MCP Server](https://devway.tistory.com/55), too. ### Installation 1. Clone the repository: ```bash git clone https://github.com/jikime/py-mcp-naver-search.git cd py-mcp-naver-search ``` 2. uv installation ```bash curl -LsSf https://astral.sh/uv/install.sh | sh ``` 3. Create a virtual environment and install dependencies: ```bash uv venv -p 3.12 source .venv/bin/activate pip install -r requirements.txt ``` 4. 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 1. Build the Docker image: ```bash docker build -t py-mcp-naver-search . ``` 2. Run the container: ```bash docker run py-mcp-naver-search ``` #### Using Local 1. Run the server: ```bash mcp run server.py ``` 2. Run the MCP Inspector ```bash mcp dev server.py ``` ## Configure MCP Settings Add the server configuration to your MCP settings file: #### Claude desktop app 1. To install automatically via [Smithery](https://smithery.ai/server/@jikime/py-mcp-naver-search): ```bash npx -y @smithery/cli install @jikime/py-mcp-naver-search --client claude ``` 2. To install manually open `~/Library/Application Support/Claude/claude_desktop_config.json` Add this to the `mcpServers` object: ```json { "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: ```json { "mcpServers": { "Google Toolbox": { "command": "/path/to/bin/uv", "args": [ "--directory", "/path/to/py-mcp-naver-search", "run", "server.py" ] } } } ``` #### for Docker ```json { "mcpServers": { "Google Toolbox": { "command": "docker", "args": [ "run", "-i", "--rm", "py-mcp-naver-search" ] } } } ``` ### Using the Client The repository includes a client script for testing: ```bash # 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: 1. `blog` - Blog posts 2. `news` - News articles 3. `book` - Books 4. `adult` - Adult content check 5. `encyc` - Encyclopedia entries 6. `cafe_article` - Cafe articles 7. `kin` - Knowledge iN Q&A 8. `local` - Local business information 9. `errata` - Keyboard input error correction 10. `shop` - Shopping items 11. `doc` - Academic papers and documents 12. `image` - Images 13. `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 - [Naver Search API MCP Server Blog](https://devway.tistory.com/55) - [Naver Open API](https://developers.naver.com/docs/search/blog/) - [MCP Protocol](https://github.com/mcp-foundation/mcp-spec) ## License This project is licensed under the MIT License - see the LICENSE file for details.