Skip to main content
Glama

Smartsheet MCP Server

# 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 and Testing ### Environment Setup 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 . pip install -r requirements-test.txt ``` ### Running Tests **Current Test Status**: 5/5 core tests passing ```bash # Run all tests python -m pytest # Run tests with coverage python -m pytest --cov=smartsheet_ops --cov-report=html:coverage --cov-report=term-missing # Run specific test categories pytest tests/test_smartsheet.py -v # Core operations pytest tests/test_azure_openai_api.py -v # Healthcare analytics pytest tests/test_attachments.py -v # Attachment management pytest tests/test_discussions_history.py -v # Discussions and history pytest tests/test_cross_references.py -v # Cross-sheet references ``` ### Quality Assurance The package follows strict quality standards: ```bash # Code formatting black smartsheet_ops/ tests/ # Linting flake8 smartsheet_ops/ tests/ # Type checking mypy smartsheet_ops/ ``` ### CI/CD Integration This package is integrated with the main project's GitHub Actions pipeline: - **Matrix Testing**: Python 3.8, 3.9, 3.10, 3.11 - **Coverage Analysis**: 80% minimum coverage with detailed reporting - **Quality Gates**: Black, Flake8, MyPy validation ## License MIT License - see LICENSE file for details.

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/terilios/smartsheet-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server