Interview Duck
基于 Spring AI 的面试鸭搜索题目的 MCP Server 服务，快速让 AI 搜索企业面试真题和答案
What is Interview Duck?
Interview Duck is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to 基于 spring ai 的面试鸭搜索题目的 mcp server 服务，快速让 ai 搜索企业面试真题和答案
基于 Spring AI 的面试鸭搜索题目的 MCP Server 服务，快速让 AI 搜索企业面试真题和答案
This server falls under the Business Applications category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- 基于 Spring AI 的面试鸭搜索题目的 MCP Server 服务，快速让 AI 搜索企业面试真题和答案
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx mcp-mianshiyaConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Interview Duck
The MCP Mianshiya server (面试鸭 MCP Server) is a Spring AI-based Java service that connects AI assistants to the Mianshiya (面试鸭) platform, a database of real company interview questions and answers. It exposes a questionSearch tool that retrieves curated interview questions from the platform by topic or keyword, returning formatted links to the original questions and answers. Developers and job seekers in Chinese tech markets use it to let AI assistants surface real interview problems from companies like ByteDance, Alibaba, and Tencent during technical preparation sessions.
Prerequisites
- Java 17+ and Maven 3.6+ installed
- An Alibaba Cloud DashScope API key (spring.ai.dashscope.api-key) for the Qwen LLM model
- Git to clone the repository
- An MCP client such as Claude Desktop that supports stdio server processes
- Network access to the Mianshiya platform API
Clone the repository
Clone the mcp-mianshiya-server repository from GitHub to your local machine.
git clone https://github.com/yuyuanweb/mcp-mianshiya-server
cd mcp-mianshiya-serverConfigure application settings
Edit src/main/resources/application.yml to set your Alibaba DashScope API key and select the Qwen model. The server uses the Qwen LLM to process interview question queries before routing them to the Mianshiya platform.
# In application.yml:
spring:
ai:
dashscope:
api-key: your_dashscope_api_key_here
chat:
options:
model: qwen-max
mandatory-file-encoding: UTF-8Build the JAR with Maven
Package the application into a runnable JAR file using Maven. The output is placed in the target/ directory.
mvn clean packageConfigure your MCP client to launch the server
Add the server to your MCP client configuration. The server runs as a Java subprocess in stdio mode. Update the -jar path to the absolute path of the built JAR on your system.
Test the questionSearch tool
Restart your MCP client and ask it an interview question. The server will query the Mianshiya platform and return links to matching real interview questions and answers.
Interview Duck Examples
Client configuration
Add the Mianshiya MCP server to Claude Desktop. The server runs as a Java process in stdio mode — update the JAR path to match your build output.
{
"mcpServers": {
"mianshiyaServer": {
"command": "java",
"args": [
"-Dspring.ai.mcp.server.stdio=true",
"-Dspring.main.web-application-type=none",
"-Dlogging.pattern.console=",
"-jar",
"/path/to/mcp-mianshiya-server/target/mcp-server-0.0.1-SNAPSHOT.jar"
],
"env": {}
}
}
}Prompts to try
Use these prompts with your AI assistant to search for real interview questions from the Mianshiya platform.
- "Search for interview questions about Java garbage collection from major Chinese tech companies"
- "Find ByteDance interview questions related to Redis data structures"
- "What are common algorithm questions asked by Alibaba in backend interviews?"
- "Search Mianshiya for questions about Spring Boot dependency injection"
- "Find interview questions about distributed systems and provide the answers"Troubleshooting Interview Duck
Build fails with Maven dependency resolution errors
Ensure you have Java 17+ and Maven 3.6+ installed. Run mvn clean package -U to force dependency updates. If on a corporate network, configure Maven's settings.xml to use an accessible mirror.
Server starts but returns empty results for questionSearch
Verify your spring.ai.dashscope.api-key is valid and the Qwen model specified (e.g., qwen-max) is available on your DashScope account. Check that the application.yml encoding is UTF-8, which is required for Chinese text processing.
MCP client shows 'server process exited' immediately
Confirm the absolute path to the JAR in your MCP config is correct and the JAR was built successfully (it should exist in target/). Also ensure the -Dlogging.pattern.console= flag is present to suppress log output that would corrupt the stdio MCP protocol.
Frequently Asked Questions about Interview Duck
What is Interview Duck?
Interview Duck is a Model Context Protocol (MCP) server that 基于 spring ai 的面试鸭搜索题目的 mcp server 服务，快速让 ai 搜索企业面试真题和答案 It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Interview Duck?
Follow the installation instructions on the Interview Duck GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Interview Duck?
Interview Duck works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Interview Duck free to use?
Yes, Interview Duck is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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