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chatExcel - 基于模型上下文协议(MCP)的Excel智能处理与数据分析服务器,专为Excel文件智能解析、数据处理、代码执行以及交互式图表生成而设计。支持复杂Excel格式处理、智能参数推荐、代码模板生成和高级数据可视化。
Configuration
View docs{
"mcpServers": {
"lillard01-chatexcel-mcp": {
"command": "python3",
"args": [
"server.py"
],
"env": {
"MCP_LOG_LEVEL": "INFO",
"MCP_SERVER_HOST": "localhost",
"MCP_SERVER_PORT": "8080",
"EXCEL_CACHE_ENABLED": "true",
"EXCEL_MAX_FILE_SIZE": "100MB",
"EXCEL_GO_SERVICE_URL": "http://localhost:8081",
"CODE_EXECUTION_TIMEOUT": "30"
}
}
}
}You have a high-performance MCP server for Excel file processing, analysis, and visualization. It runs multiple specialized tools across Python and Go engines, supports secure code execution, formula parsing, data quality checks, and rich visualization, and is designed for enterprise-grade reliability and scalability.
Connect your MCP client to the server to perform Excel data workflows end-to-end. You can explore file metadata, read and transform data, run code that processes Excel data safely, create charts, validate data quality, and compute complex Excel formulas with dependency analysis. Start with a simple read of an Excel file, then layer in cleaning, analysis, visualization, and formula calculations as needed for your tasks.
Prerequisites: you need Python 3.11+ installed on your system. You may also optionally use Go for the high-performance Excel engine.
Step 1. Set up a virtual environment and install dependencies.
Step 2. Start the MCP server (basic) using the standard server script.
# Create and activate a virtual environment
python3 -m venv venv
source venv/bin/activate # macOS/Linux
# Windows users: venv\Scripts\activate
# Install dependencies
pip install -r requirements.txt
# Start the standard MCP server
python server.pyOperate all code execution within a sandboxed environment and enforce strict security checks for formulas. Configure access controls, audit logs, and resource limits to protect your system when running user-provided code or processing sensitive data.
Common workflows include reading Excel metadata, selecting optimal read parameters, performing data cleaning and transformation, running analysis code, producing interactive charts, validating data quality, and computing Excel formulas with dependency analysis.
CSV file metadata reading and intelligent analysis with encoding detection, delimiter recognition, and data statistics
Excel file metadata reading and integrity validation across multiple sheets
Enhanced Excel reading with Go engine integration and smart parameter suggestion
Enhanced Excel file information retrieval with sheet counts and structural statistics
Excel code execution engine in a safe sandbox with complex parameter support and pandas integration
CSV data code execution engine with安全环境 and data processing capabilities
Enhanced Excel writing with formatting and style support
Internal chart generation for Excel with multiple chart types and styles
Performance benchmarking between Go and Python Excel processing paths
Batch validation across multiple Excel files with concurrent processing
Interactive bar chart generation using Chart.js for HTML output
Interactive pie chart generation with animation and data labels
Interactive line chart generation for trend analysis
Data integrity verification and reconciliation with detailed reports
Data quality assessment with recommendations and scoring
Comprehensive data validation and quality assurance across datasets
Advanced, multi-stage data quality checks with deep analysis
Advanced extraction of cell content with multi-type formatting
Automated character format conversion with configurable rules
Multi-condition data extraction with flexible filtering
Smart merging of multiple tables with relationship handling
Excel data cleaning to improve quality and consistency
Parallel batch processing of Excel files with unified configuration
Excel formula parser with AST construction and security checks
Workbook compiler with code generation and dependency analysis
Safe execution of Excel formulas with context support
Formula dependency analysis and impact assessment
Formula safety and syntax validation with risk assessment