Baidu AI Search MCP Server

What does “Baidu AI Search” MCP Server do?

The Baidu AI Search MCP Server is designed to bridge AI assistants with external data sources, specifically leveraging Baidu’s search capabilities. It acts as a middleware tool, enabling AI assistants to access and retrieve information from Baidu’s search engine, which can then be incorporated into development workflows. This enhances the assistant’s ability to answer queries with up-to-date, relevant information from the web, support research tasks, and augment context for large language model (LLM) interactions. The server streamlines tasks such as querying search results, extracting knowledge, and integrating Baidu’s powerful web search into automated pipelines or conversational agents, thereby improving response quality and breadth.

List of Prompts

No prompt templates were found in the provided repository files.

List of Resources

No explicit MCP resources are documented in the provided repository files.

List of Tools

No tool definitions or implementations were found in server.py or other files within the provided URL.

Use Cases of this MCP Server

• Web Search Augmentation: Integrate real-time Baidu web search results into AI assistant responses to provide up-to-date and region-specific information.
• Research Assistance: Automate web-based research tasks by querying Baidu and extracting summaries or relevant facts for developers or end-users.
• Knowledge Base Expansion: Use Baidu search output to supplement internal databases with external knowledge, improving the AI’s comprehension and contextual understanding.
• Conversational Agents: Enhance chatbots or virtual agents by enabling them to answer questions using the latest information from Baidu’s search engine.
• Content Generation: Support creative or content generation workflows by sourcing information, references, or data points directly from the web.

How to set it up

Windsurf

1. Ensure Node.js is installed on your system.
2. Open the Windsurf configuration file (e.g., windsurf.config.json).
3. Add the Baidu AI Search MCP Server under the mcpServers section:

   {
     "mcpServers": {
       "baidu-ai-search": {
         "command": "npx",
         "args": ["@baidu/ai-search-mcp-server@latest"]
       }
     }
   }
   

4. Save your configuration and restart Windsurf.
5. Verify by opening the Windsurf dashboard and checking for “baidu-ai-search” under MCP servers.

Securing API Keys

Use environment variables to store sensitive information:

{
  "mcpServers": {
    "baidu-ai-search": {
      "command": "npx",
      "args": ["@baidu/ai-search-mcp-server@latest"],
      "env": {
        "BAIDU_API_KEY": "${BAIDU_API_KEY}"
      },
      "inputs": {
        "apiKey": "${BAIDU_API_KEY}"
      }
    }
  }
}

Claude

1. Install prerequisites (Node.js).
2. Locate and edit the Claude configuration file.
3. Add the MCP server with:

   {
     "mcpServers": {
       "baidu-ai-search": {
         "command": "npx",
         "args": ["@baidu/ai-search-mcp-server@latest"]
       }
     }
   }
   

4. Restart Claude.
5. Confirm the server is running in the Claude UI.

Cursor

1. Ensure Node.js is present.
2. Edit the Cursor configuration file.
3. Add:

   {
     "mcpServers": {
       "baidu-ai-search": {
         "command": "npx",
         "args": ["@baidu/ai-search-mcp-server@latest"]
       }
     }
   }
   

4. Save and restart Cursor.
5. Check for successful server registration.

Cline

1. Install Node.js as a prerequisite.
2. Open Cline’s configuration file.
3. Insert:

   {
     "mcpServers": {
       "baidu-ai-search": {
         "command": "npx",
         "args": ["@baidu/ai-search-mcp-server@latest"]
       }
     }
   }
   

4. Save changes, restart Cline.
5. Validate setup in the Cline interface.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "baidu-ai-search": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “baidu-ai-search” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Our opinion

Based on the available information, the MCP server has clear high-level documentation and a likely strong use case for search augmentation, but lacks visible implementation details, resources, and prompt templates in the public repository section provided. Thus, we rate this MCP a 3/10 for practical developer adoption at this time.

MCP Score