Smartsheet MCP Server

  • smartsheet_ops
# Smartsheet Operations Package Python package providing healthcare analytics operations for Smartsheet integration. ## Installation ```bash pip install -e . ``` ## Configuration Create a `.env` file with the following variables: ```env # Smartsheet API Configuration SMARTSHEET_API_KEY=your-smartsheet-api-key # Azure OpenAI Configuration AZURE_OPENAI_API_KEY=your-azure-openai-key AZURE_OPENAI_API_BASE=your-azure-openai-endpoint AZURE_OPENAI_API_VERSION=your-api-version AZURE_OPENAI_DEPLOYMENT=your-deployment-name ``` ## Usage ### Command Line Interface ```bash # Get column mapping smartsheet-ops --api-key "your-key" --sheet-id "your-sheet" --operation get_column_map # Start batch analysis smartsheet-ops --api-key "your-key" --sheet-id "your-sheet" --operation start_analysis --data '{ "type": "custom", "sourceColumns": ["Ideas"], "targetColumn": "Score", "customGoal": "Score each idea based on healthcare impact" }' ``` ### Python API ```python from smartsheet_ops import SmartsheetOperations # Initialize client ops = SmartsheetOperations(api_key="your-key") # Get column mapping result = ops.get_sheet_info(sheet_id="your-sheet") # Add rows result = ops.add_rows( sheet_id="your-sheet", row_data=[{"Column1": "Value1"}], column_map={"Column1": "col-id"} ) ``` ## Features ### Batch Analysis - Clinical note summarization - Patient feedback sentiment analysis - Protocol compliance scoring - Research impact assessment - Pediatric alignment scoring ### Data Operations - Row management (add/update/delete) - Column management - Bulk updates - Search capabilities ### Healthcare Focus - Specialized scoring systems - Clinical data processing - Research analytics - Patient feedback analysis ## Development 1. Create conda environment: ```bash conda create -n smartsheet_dev python=3.12 conda activate smartsheet_dev ``` 2. Install in development mode: ```bash pip install -e . ``` 3. Run tests: ```bash python -m pytest ``` ## License MIT License - see LICENSE file for details.