Excel表格生成工具

docker run -d \
  --name excel-mcp \
  -p 9080:8000 \
  -p 9081:8001 \
  antuelle78/excel-mcp-integration:latest

git clone https://github.com/antuelle78/excel-mcp-integration.git
cd excel-mcp-integration
pip install -r requirements.txt
python src/main.py

curl -X POST http://localhost:8000/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "method": "tools/call",
    "params": {
      "name": "create_excel_file",
      "arguments": {
        "filename": "example.xlsx",
        "headers": ["Name", "Value"],
        "sheet_data": [["Item 1", "100"], ["Item 2", "200"]]
      }
    }
  }'

# Run all tests
python -m pytest tests/ -v

# Run specific test
python -m pytest tests/integration_test.py::test_mcp_workflow -v

graph TD
    A[👤 User Request] --> B[🤖 AI Assistant]
    B --> C[🔧 Excel MCP Tools]
    C --> D[📊 Excel File Generation]
    D --> E[📁 Download Ready]
    E --> F[✅ User Downloads]

    style A fill:#e1f5fe
    style B fill:#f3e5f5
    style C fill:#e8f5e8
    style D fill:#fff3e0
    style E fill:#fce4ec
    style F fill:#e8f5e8

graph TB
    subgraph "🌐 User Interface"
        A[Open-WebUI]
        B[Custom AI Assistant]
    end

    subgraph "🔧 Excel MCP Server"
        C[MCP Protocol Handler]
        D[Excel Tools Engine]
        E[Security Validator]
        F[File Generator]
    end

    subgraph "💾 Data & Storage"
        G[Excel Templates]
        H[Output Directory]
        I[Session Cache]
    end

    subgraph "🐳 Infrastructure"
        J[Docker Container]
        K[FastAPI Server]
        L[File Server]
    end

    A --> C
    B --> C
    C --> D
    D --> E
    E --> F
    F --> H
    D --> I
    J --> K
    J --> L

    style A fill:#e3f2fd
    style C fill:#f3e5f5
    style D fill:#e8f5e8
    style J fill:#fff3e0

# 🚀 One-command deployment!
docker run -d \
  --name excel-mcp \
  -p 9080:8000 \
  -p 9081:8001 \
  antuelle78/excel-mcp-integration:latest

# ✅ Check status
docker ps | grep excel-mcp

# 🎯 Test connection
curl http://excelgen.e-cancer.fr:31006/mcp

# 📄 docker-compose.yml
version: '3.8'
services:
  excel-mcp:
    image: antuelle78/excel-mcp-integration:latest
    container_name: excel-mcp-server
    ports:
      - "9080:8000"  # MCP Server
      - "9081:8001"  # File Server
    volumes:
      - ./output:/app/output
    environment:
      - MAX_ROWS=10000
      - MAX_COLS=100
    restart: unless-stopped

# 🚀 Deploy the stack
docker compose up -d

# 📊 Monitor logs
docker compose logs -f excel-mcp

# 📥 Get the code
git clone https://github.com/antuelle78/excel-mcp-integration.git
cd excel-mcp-integration

# 🐍 Create virtual environment
python3 -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate

# 📦 Install dependencies
pip install -r requirements.txt

# Terminal 1: Start MCP Server
python src/main.py

# Terminal 2: Start File Server (optional)
python -m http.server 8001 -d output/

# 🎯 Server ready at: http://localhost:8000/mcp

curl -X POST http://localhost:8000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -d '{
    "jsonrpc": "2.0",
    "id": "test",
    "method": "tools/call",
    "params": {
      "name": "create_excel_file",
      "arguments": {
        "filename": "hello_world.xlsx",
        "headers": ["Message", "Status"],
        "sheet_data": [["Hello", "Success"], ["World", "Ready"]]
      }
    }
  }'

{
  "jsonrpc": "2.0",
  "id": "test",
  "result": {
    "content": [{
      "type": "text",
      "text": "Successfully created Excel file: output/hello_world.xlsx"
    }]
  }
}

# 🚀 Production-ready configuration
export HOST=0.0.0.0
export PORT=9080
export FILE_SERVER_PORT=9081
export OUTPUT_DIR=/app/output
export MAX_ROWS=50000
export MAX_COLS=500

# 🔒 Security settings
export ALLOWED_EXTENSIONS=".xlsx,.xls"
export MAX_FILE_SIZE=10485760  # 10MB

# 📊 Performance tuning
export WORKER_COUNT=4
export TIMEOUT=300

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "create_excel_file",
    "arguments": {
      "filename": "employee_roster.xlsx",
      "headers": ["Name", "Department", "Salary", "Start Date"],
      "sheet_data": [
        ["Alice Johnson", "Engineering", "$85,000", "2023-01-15"],
        ["Bob Smith", "Marketing", "$72,000", "2023-03-01"],
        ["Carol Davis", "Sales", "$68,000", "2023-02-10"]
      ],
      "sheet_name": "Employee Directory",
      "formatting": {
        "header_bold": true,
        "header_background": "4472C4",
        "alternate_row_colors": true
      }
    }
  }
}

{
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "name": "create_excel_chart",
    "arguments": {
      "filename": "sales_data.xlsx",
      "chart_type": "bar",
      "data_range": "A1:C13",
      "title": "Monthly Sales Performance",
      "sheet_name": "Sales"
    }
  }
}

# 🤖 Your AI becomes an Excel expert
User: "Create a sales report for Q4 with charts"
Assistant: "I'll create a professional Excel file with your Q4 sales data and charts."

# 📊 Result: Perfectly formatted Excel file with charts!

// 🛠️ Configure in Open-WebUI Admin Panel
{
  "name": "Excel Creator",
  "description": "Create professional Excel spreadsheets",
  "tools": ["create_excel_file", "create_excel_chart"]
}

User: "I need a budget spreadsheet for next quarter with categories for marketing, sales, and operations"

Assistant: "I'll create a comprehensive budget spreadsheet with proper formatting and calculations."

[AI processes request through Excel MCP]

Result: "✅ Budget spreadsheet created! Download: budget_q1_2024.xlsx"
- Professional formatting with headers
- Auto-calculations for totals
- Color-coded categories
- Ready for executive review

User: "Generate a test data spreadsheet with 100 rows of user information"

Assistant: "Creating a comprehensive test dataset with realistic user information."

[AI generates structured data through Excel MCP]

Result: "✅ Test data spreadsheet ready! Download: test_users.xlsx"
- 100 rows of realistic data
- Proper data types and validation
- Exportable for testing frameworks
- Includes edge cases and variations

User: "Create a dashboard spreadsheet showing KPI trends with charts"

Assistant: "I'll build a professional KPI dashboard with multiple chart types."

[AI creates advanced Excel with charts]

Result: "✅ KPI Dashboard created! Download: kpi_dashboard.xlsx"
- Multiple chart types (bar, line, pie)
- Trend analysis calculations
- Professional styling
- Interactive filters

# 🧪 Run all tests
python -m pytest tests/ -v

# 🔍 Test specific functionality
python tests/test_core.py          # Core Excel features
python tests/test_mcp.py           # MCP protocol
python tests/test_openwebui.py     # AI integration

# 🌐 Test API endpoints
curl -X POST http://localhost:9080/mcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/list"}'

# 📊 Test file generation
curl -X POST http://localhost:9080/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "method": "tools/call",
    "params": {
      "name": "create_excel_file",
      "arguments": {
        "filename": "test.xlsx",
        "headers": ["Test"],
        "sheet_data": [["Success"]]
      }
    }
  }'

# 📦 Pull & Run (Production Ready)
docker run -d \
  --name excel-mcp \
  -p 9080:8000 \
  -p 9081:8001 \
  antuelle78/excel-mcp-integration:latest

# ✅ Verify deployment
curl http://excelgen.e-cancer.fr:31006/mcp

# 📄 docker-compose.yml (Full Stack)
version: '3.8'
services:
  excel-mcp:
    image: antuelle78/excel-mcp-integration:latest
    container_name: excel-mcp-server
    ports:
      - "9080:8000"  # MCP Server
      - "9081:8001"  # File Server
    volumes:
      - ./output:/app/output
      - ./logs:/app/logs
    environment:
      - HOST=0.0.0.0
      - MAX_ROWS=50000
      - MAX_COLS=500
      - LOG_LEVEL=INFO
    restart: unless-stopped
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8000/mcp"]
      interval: 30s
      timeout: 10s
      retries: 3

# 📦 Deploy to Kubernetes
kubectl apply -f excel-mcp-deployment.yaml

# ✅ Verify deployment
kubectl get pods
kubectl get services

# 🌐 Access your service
curl http://excelgen.e-cancer.fr:31006/mcp

# 📄 excel-mcp-deployment.yaml (Production Ready)
apiVersion: apps/v1
kind: Deployment
metadata:
  name: excel-mcp
spec:
  replicas: 1
  template:
    spec:
      containers:
      - name: excel-mcp
        image: antuelle78/excel-mcp-integration:latest
        ports:
        - containerPort: 8000  # MCP Server
        - containerPort: 8001  # File Server
        envFrom:
        - configMapRef:
            name: excel-mcp-config
        volumeMounts:
        - name: output-storage
          mountPath: /app/output
---
apiVersion: v1
kind: Service
metadata:
  name: excel-mcp-service
spec:
  type: NodePort
  ports:
  - port: 8000
    targetPort: 8000
    nodePort: 31006  # External access
  - port: 8001
    targetPort: 8001
    nodePort: 31007  # File downloads

{
  "api_config": {
    "base_url": "http://excel-mcp-service.excel-mcp.svc.cluster.local:8000",
    "endpoints": {
      "create_excel_file": {
        "url": "/mcp",
        "method": "POST"
      }
    }
  }
}

excel-mcp-integration/
├── 📁 src/                    # 🚀 Core source code
│   ├── main.py               # Main MCP server
│   ├── excel_assistant_pipe.py # Open-WebUI pipe function (Docker)
│   ├── excel_assistant_pipe_k8s.py # Open-WebUI pipe function (Kubernetes)
│   └── web_api_wrapper.py    # REST API wrapper
├── 📁 tests/                  # 🧪 Test suite (23 scenarios)
│   ├── test_core.py          # Core functionality
│   ├── test_mcp.py           # Protocol tests
│   └── test_openwebui.py     # Integration tests
├── 📁 docs/                   # 📖 Documentation
│   ├── OPENWEBUI_SETUP.md    # Integration guides
│   ├── DEPLOYMENT_GUIDE.md   # Deployment instructions
│   └── test_prompts.md       # Test scenarios
├── 📁 config/                 # ⚙️ Configuration files
│   ├── openwebui_tools.json  # Tool definitions (Docker)
│   ├── openwebui_tools_k8s.json # Tool definitions (Kubernetes)
│   ├── openwebui_functions.json # Function definitions (Docker)
│   ├── openwebui_functions_k8s.json # Function definitions (Kubernetes)
│   ├── openwebui_tools_enhanced.json # Enhanced tools (Docker)
│   ├── openwebui_tools_enhanced_k8s.json # Enhanced tools (Kubernetes)
│   └── pipe_requirements.txt # Dependencies
├── 🐳 Dockerfile             # Container build
├── 🐙 docker-compose.yml     # Orchestration
└── 📊 output/                # Generated Excel files

# Test MCP server
curl -v http://localhost:9080/mcp

# Test file server
curl -I http://localhost:9081/files/

# Check Docker logs
docker logs excel-mcp

# Check output directory
ls -la output/

# Verify file permissions
chmod 755 output/

# Test with minimal data
curl -X POST http://localhost:9080/mcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"create_excel_file","arguments":{"filename":"test.xlsx","headers":["Test"],"sheet_data":[["OK"]]}}}'

# Check Open-WebUI logs
docker logs open-webui

# Test tool configuration
curl http://localhost:8080/api/tools

# Verify model loading
ollama list

graph LR
    A[Fork Repository] --> B[Create Feature Branch]
    B --> C[Make Changes]
    C --> D[Add Tests]
    D --> E[Update Documentation]
    E --> F[Commit Changes]
    F --> G[Push Branch]
    G --> H[Open Pull Request]
    H --> I[Code Review]
    I --> J[Merge to Main]