
ModelContextProtocol (MCP) Server Integration
The ModelContextProtocol (MCP) Server acts as a bridge between AI agents and external data sources, APIs, and services, enabling FlowHunt users to build context...

Seamlessly bridge AI assistants with property management systems for smarter automation and data access with CRIC物业AI MCP Server.
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.
No prompt templates were found in the repository or documentation.
No explicit resources are documented in the repository or documentation.
No tool definitions were found in server.py or equivalent files.
{
"mcpServers": {
"cric-wuye-ai": {
"command": "npx",
"args": ["@wuye-ai/mcp-server-wuye-ai@latest"]
}
}
}
{
"mcpServers": {
"cric-wuye-ai": {
"command": "npx",
"args": ["@wuye-ai/mcp-server-wuye-ai@latest"]
}
}
}
{
"mcpServers": {
"cric-wuye-ai": {
"command": "npx",
"args": ["@wuye-ai/mcp-server-wuye-ai@latest"]
}
}
}
{
"mcpServers": {
"cric-wuye-ai": {
"command": "npx",
"args": ["@wuye-ai/mcp-server-wuye-ai@latest"]
}
}
}
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}}"
}
}
}
}
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.
| Section | Availability | Details/Notes |
|---|---|---|
| Overview | ✅ | |
| List of Prompts | ⛔ | None found |
| List of Resources | ⛔ | Not documented |
| List of Tools | ⛔ | Not found |
| Securing API Keys | ✅ | Config example given |
| Sampling Support (less important in evaluation) | ⛔ | Not specified |
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.
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.
| Has a LICENSE | ⛔ |
|---|---|
| Has at least one tool | ⛔ |
| Number of Forks | 2 |
| Number of Stars | 1 |
Empower your property management workflows with AI-driven automation and secure API access. Get started with CRIC物业AI MCP Server for streamlined integration in FlowHunt.

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