Chatbi MCP Server
ChatBI MCP Server is an LLM - based data analysis service that supports code generation, data statistics, and visualization through natural language instructions, and can be integrated with client tools to achieve automated analysis.
rating : 2.5 points
downloads : 6.0K
What is ChatBI MCP Server?
ChatBI MCP Server is an intelligent data analysis service that understands your natural language instructions through large language models, automatically generates and executes data analysis code, and helps you quickly gain data insights.How to use ChatBI MCP Server?
Simply connect to the service through a compatible client (such as Cherry Studio), describe your analysis requirements in natural language, and the system will automatically complete the entire process from data query to visual presentation.Applicable scenarios
Suitable for scenarios such as business intelligence analysis, data exploration, and automated report generation. It is particularly suitable for business personnel who need to quickly obtain data insights but lack programming skills.Main features
Automatic code generation
Automatically generate Python code for data analysis based on natural language instructions
Intelligent data analysis
Support various analysis types such as statistical analysis, data pivoting, and trend prediction
Visualization integration
Integrate with mcp - server - chart to support automatic chart generation
Automatic error handling
Automatically attempt to correct when the generated code has problems
Advantages
Perform complex data analysis without programming skills
Support multiple large language models (GLM4.5, Qwen, etc.)
High degree of automation, complete from analysis to visualization with one click
Can be integrated into existing BI workflows
Limitations
Require strong LLM model support (Qwen3 - 32B and above)
Complex analysis may require a long response time
Technical knowledge is required for the initial configuration
How to use
Configure the environment
Copy the environment configuration file and set the LLM API key
Install dependencies
Create a Python virtual environment and install the required dependency packages
Start the service
Enter the src directory and start the service
Client configuration
Configure the server connection in a client that supports the MCP protocol (such as Cherry Studio)
Usage examples
Regular statistical analysis
Perform basic data statistics and aggregation analysis
Data visualization
Generate interactive data charts
Comprehensive analysis
Perform multi - step data analysis and generate reports
Frequently Asked Questions
What kind of LLM model is required?
Why is my query response slow?
How to verify that the service is working properly?
What is the default verification information?
Related resources
Visualization component library
MCP server chart components for data visualization
Configuration example screenshot
Example of the client configuration interface
Usage example screenshot
Example of comprehensive analysis results

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