Verodat Mcp 伺服器

什麼是 Verodat MCP 伺服器？

Verodat MCP 伺服器是一個開源項目，旨在提供一個穩健且可擴展的伺服器解決方案，用於管理和處理數據。它特別適合希望實施集中數據管理系統的組織，能夠高效處理各種數據類型和工作流程。該伺服器專注於性能、可靠性以及與現有系統的集成便利性。

Verodat MCP 伺服器的特點

• 可擴展性：該伺服器能夠處理不斷增加的數據和用戶請求，而不會妨礙性能。
• 數據管理：它提供全面的數據存儲、檢索和處理工具，非常適合依賴數據驅動決策的企業。
• 開源：作為一個開源項目，它允許開發者根據特定需求自定義和擴展其功能。
• 用戶友好的界面：該伺服器配備直觀的界面，簡化了數據和伺服器設置的管理。
• 社區支持：作為開源生態系統的一部分，用戶可以受益於社區貢獻、文檔和支持。

如何使用 Verodat MCP 伺服器

1. 安裝：首先從官方庫下載伺服器。按照文檔中提供的安裝說明在您的伺服器環境中設置它。
2. 配置：安裝後，根據您的組織需求配置伺服器設置。這包括設置用戶權限、數據存儲選項以及與其他系統的集成。
3. 數據管理：使用伺服器的界面上傳、管理和處理您的數據。您可以創建自動化數據處理任務的工作流程。
4. 監控和維護：定期監控伺服器性能並進行維護，以確保最佳運行。利用社區資源進行故障排除和更新。

常見問題解答

Verodat MCP 伺服器使用了哪些編程語言？

Verodat MCP 伺服器主要使用 [在此插入編程語言] 開發，這些語言以其性能和可擴展性而聞名。

使用 Verodat MCP 伺服器需要付費嗎？

不需要，Verodat MCP 伺服器是開源且免費使用的。然而，您可能會產生與託管和維護相關的費用。

我可以為 Verodat MCP 伺服器項目做貢獻嗎？

當然可以！歡迎貢獻。您可以通過報告問題、提交代碼或改善文檔來參與該項目，通過項目的 GitHub 倉庫進行。

我如何獲得 Verodat MCP 伺服器的支持？

支持可以通過社區論壇、GitHub 問題和文檔獲得。您還可以與其他用戶和開發者聯繫以獲得幫助。

Verodat MCP 伺服器適合小型企業嗎？

是的，Verodat MCP 伺服器設計為可擴展，適合小型企業和大型企業。其靈活性使其能夠適應各種業務規模和需求。

Verodat MCP Server

Overview

A Model Context Protocol (MCP) server implementation for Verodat, enabling seamless integration of Verodat's data management capabilities with AI systems like Claude Desktop.

Verodat MCP Server

This repository contains a Model Context Protocol (MCP) server implementation for Verodat, allowing AI models to interact with Verodat's data management capabilities through well-defined tools.

Overview

The Verodat MCP Server provides a standardized way for AI models to access and manipulate data in Verodat. It implements the Model Context Protocol specification, providing tools for data consumption, design, and management.

Tool Categories

The server is organized into three main tool categories, each offering a progressive set of capabilities:

1. Consume (8 tools)

The base category focused on data retrieval operations:

• get-accounts: Retrieve available accounts
• get-workspaces: List workspaces within an account
• get-datasets: List datasets in a workspace
• get-dataset-output: Retrieve actual data from a dataset
• get-dataset-targetfields: Retrieve field definitions for a dataset
• get-queries: Retrieve existing AI queries
• get-ai-context: Get workspace context and data structure
• execute-ai-query: Execute AI-powered queries on datasets

2. Design (9 tools)

Includes all tools from Consume, plus:

• create-dataset: Create a new dataset with defined schema

3. Manage (10 tools)

Includes all tools from Design, plus:

• upload-dataset-rows: Upload data rows to existing datasets

Prerequisites

• Node.js (v18 or higher)
• Git
• Claude Desktop (for Claude integration)
• Verodat account and AI API key

Installation

Quick Start

Installing via Smithery

To install Verodat MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @Verodat/verodat-mcp-server --client claude

Manual Installation

1. Clone the repository:

git clone https://github.com/Verodat/verodat-mcp-server.git
cd verodat-mcp-server

2. Install dependencies and build:

npm install
npm run build

3. Configure Claude Desktop: Create or modify the config file:
   • MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%/Claude/claude_desktop_config.json
   Add the configuration which is mensioned below in configuration:

Getting Started with Verodat

1. Sign up for a Verodat account at verodat.com
2. Generate an AI API key from your Verodat dashboard
3. Add the API key to your Claude Desktop configuration

Configuration

The server requires configuration for authentication and API endpoints. Create a configuration file for your AI model to use:

{
  "mcpServers": {
    "verodat-consume": {
      "command": "node",
      "args": [
        "path/to/verodat-mcp-server/build/src/consume.js"
      ],
      "env": {
        "VERODAT_AI_API_KEY": "your-api-key",
        "VERODAT_API_BASE_URL": "https://verodat.io/api/v3"
      }
    }
  }
}

Configuration Options

You can configure any of the three tool categories by specifying the appropriate JS file one at a time in claude:

• Consume only: Use consume.js (8 tools for data retrieval)
• Design capabilities: Use design.js (9 tools, includes dataset creation)
• Full management: Use manage.js (10 tools, includes data upload)

Example for configuring all three categories simultaneously:

{
  "mcpServers": {
    "verodat-consume": {
      "command": "node",
      "args": [
        "path/to/verodat-mcp-server/build/src/consume.js"
      ],
      "env": {
        "VERODAT_AI_API_KEY": "your-api-key",
        "VERODAT_API_BASE_URL": "https://verodat.io/api/v3"
      }
    },
    "verodat-design": {
      "command": "node",
      "args": [
        "path/to/verodat-mcp-server/build/src/design.js"
      ],
      "env": {
        "VERODAT_AI_API_KEY": "your-api-key",
        "VERODAT_API_BASE_URL": "https://verodat.io/api/v3"
      }
    },
    "verodat-manage": {
      "command": "node",
      "args": [
        "path/to/verodat-mcp-server/build/src/manage.js"
      ],
      "env": {
        "VERODAT_AI_API_KEY": "your-api-key",
        "VERODAT_API_BASE_URL": "https://verodat.io/api/v3"
      }
    }
  }
}

Environment Variables

• VERODAT_AI_API_KEY: Your Verodat API key for authentication
• VERODAT_API_BASE_URL: The base URL for the Verodat API (defaults to "https://verodat.io/api/v3" if not specified)

Tool Usage Guide

Available Commands

The server provides the following MCP commands:

// Account & Workspace Management
get-accounts        // List accessible accounts
get-workspaces      // List workspaces in an account
get-queries         // Retrieve existing AI queries

// Dataset Operations
create-dataset      // Create a new dataset
get-datasets        // List datasets in a workspace
get-dataset-output  // Retrieve dataset records
get-dataset-targetfields // Retrieve dataset targetfields
upload-dataset-rows // Add new data rows to an existing dataset

// AI Operations
get-ai-context      // Get workspace AI context
execute-ai-query    // Run AI queries on datasets

Selecting the Right Tool Category

• For read-only operations: Use the consume.js server configuration
• For creating datasets: Use the design.js server configuration
• For uploading data: Use the manage.js server configuration

Security Considerations

• Authentication is required via API key
• Request validation ensures properly formatted data

Development

The codebase is written in TypeScript and organized into:

• Tool handlers: Implementation of each tool's functionality
• Transport layer: Handles communication with the AI model
• Validation: Ensures proper data formats using Zod schemas

Debugging

The MCP server communicates over stdio, which can make debugging challenging. We provide an MCP Inspector tool to help:

npm run inspector

This will provide a URL to access debugging tools in your browser.

Contributing

We welcome contributions! Please feel free to submit a Pull Request.

License

LICENSE file for details

Support

• Documentation: Verodat Docs
• Issues: GitHub Issues
• Community: Verodat Community