CRIC物业AI MCP Server

What does “CRIC物业AI” MCP Server do?

CRIC物业AI MCP Server is designed to serve as a bridge between AI assistants and external property management data, APIs, or services. By leveraging the Model Context Protocol (MCP), this server enables AI-driven tools and agents to execute workflows such as querying property databases, managing files, or interacting with third-party APIs relevant to property management. The CRIC物业AI MCP Server streamlines access to structured information and operational tools, making it easier for developers and organizations to automate and enhance property management tasks through AI-powered applications. Its integration capabilities allow for improved efficiency and standardized interactions between AI clients and diverse backend services.

List of Prompts

No prompt templates were found in the repository or documentation.

List of Resources

No explicit resources are documented in the repository or documentation.

List of Tools

No tool definitions were found in server.py or equivalent files.

Use Cases of this MCP Server

• Property Data Querying: Enables AI agents to query up-to-date property management information for analytics and reporting.
• Workflow Automation: Facilitates the automation of routine tasks in property management through integration with external services.
• API Integration: Provides endpoints for connecting property management platforms with other software solutions.
• File/Data Management: Supports file operations and structured data management for property-related documents.
• AI Assistant Enhancement: Empowers virtual assistants with context-aware actions for property management scenarios.

How to set it up

Windsurf

1. Ensure Node.js is installed on your machine.
2. Open your Windsurf configuration file.
3. Add the CRIC物业AI MCP Server using the following JSON snippet:

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

4. Save the configuration and restart Windsurf.
5. Verify the server is running in the Windsurf UI.

Claude

1. Install Node.js if not already present.
2. Edit Claude’s configuration file to include the MCP server.
3. Insert the following under the mcpServers section:

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

4. Save your changes and restart Claude.
5. Confirm the server is active via Claude’s interface.

Cursor

1. Prerequisite: Node.js installed.
2. Access the Cursor configuration file.
3. Add:

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

4. Save and restart Cursor.
5. Check that CRIC物业AI MCP Server appears in the tool list.

Cline

1. Make sure Node.js is installed.
2. Find and edit the configuration file for Cline.
3. Insert:

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

4. Save and restart Cline.
5. Verify the server is available from within Cline.

Securing API Keys Example:

To securely manage API keys or secrets, use environment variables in your configuration:

{
  "mcpServers": {
    "cric-wuye-ai": {
      "command": "npx",
      "args": ["@wuye-ai/mcp-server-wuye-ai@latest"],
      "env": {
        "API_KEY": "${{secrets.CRICSERVICE_API_KEY}}"
      },
      "inputs": {
        "apiKey": "${{secrets.CRICSERVICE_API_KEY}}"
      }
    }
  }
}

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:

{
  "cric-wuye-ai": {
    "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 “cric-wuye-ai” to the actual name of your MCP server and replace the URL with your own MCP server URL.

Overview

Between the thorough setup instructions, basic use-case examples, and lack of detail on resources, prompts, and tools, this MCP server appears to provide foundational integration but lacks documentation depth. The absence of Roots and Sampling details limits advanced evaluation.

Our opinion

This MCP server is straightforward to set up and integrates well with common platforms, but it lacks detail about prompts, resources, and tools, which reduces its flexibility and ease of adoption for developers seeking ready-to-use features. We would rate this MCP server a 4/10 for overall developer experience and documentation completeness.

MCP Score