Smartsheet MCP Server
@terilios
关于 Smartsheet MCP Server
MCP server providing healthcare analytics capabilities for Smartsheet, including clinical note summarization, patient feedback analysis, and research impact assessment
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"smartsheet-server": {
"command": "node",
"args": [
"build/index.js"
],
"env": {
"PYTHON_PATH": "/Users/[username]/anaconda3/envs/cline_mcp_env/bin/python3",
"SMARTSHEET_API_KEY": "your-api-key"
}
}
}
}工具
未检测到工具
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is Smartsheet MCP Server?
An MCP server that integrates with Smartsheet to enable automated operations on Smartsheet documents through a standardized interface, bridging AI-powered automation tools with Smartsheet's collaboration platform.
How to use Smartsheet MCP Server?
Install and configure the server using the provided setup scripts. The server communicates via the MCP protocol over stdio. Authentication requires a Smartsheet API token. Specific command-line invocation details are not described in the README.
Key features of Smartsheet MCP Server
- 34 tools for Smartsheet operations including read, write, update, delete, and search.
- Column management: add, rename, and delete columns with dependency checking.
- Batch analysis using Azure OpenAI for healthcare and research data.
- Attachment, discussion, and comment management on sheets and rows.
- Cell history and row audit trails with user attribution.
- Cross-sheet reference analysis and formula dependency tracking.
Use cases of Smartsheet MCP Server
- Clinical research analytics including protocol compliance scoring and patient data analysis.
- Hospital operations such as resource utilization and quality metrics tracking.
- Automated document management with dynamic column creation and validation.
- Bulk data updates with integrity checks and duplicate detection.
- AI-driven sheet customization and automated reporting workflows.
FAQ from Smartsheet MCP Server
What runtime dependencies does it require?
Node.js versions 16, 18, or 20, and Python versions 3.8, 3.9, 3.10, or 3.11 are supported.
How does it handle data integrity?
Enforces validation rules, maintains referential integrity, preserves formula references, and implements comprehensive error handling.
What transport method does it use?
It communicates via the MCP protocol over a stdio interface.
Does it support batch operations?
Yes, tools like smartsheet_bulk_update and start_batch_analysis support batch processing with configurable sizes and progress tracking.
Are there any column limits?
The server enforces a column limit of 400 per sheet with validation when adding columns.
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