Verodat Mcp 服务器

什么是 Verodat MCP 服务器？

Verodat MCP 服务器是一个开源项目，旨在提供一个强大且可扩展的服务器解决方案，用于管理和处理数据。它特别适合希望实施集中数据管理系统的组织，能够高效处理各种数据类型和工作流程。该服务器专注于性能、可靠性以及与现有系统的集成便利性。

Verodat MCP 服务器的特点

• 可扩展性：该服务器能够处理不断增加的数据量和用户请求，而不会影响性能。
• 数据管理：它提供全面的数据存储、检索和处理工具，非常适合依赖数据驱动决策的企业。
• 开源：作为一个开源项目，它允许开发人员根据特定需求自定义和扩展其功能。
• 用户友好的界面：该服务器配备直观的界面，简化了数据和服务器设置的管理。
• 社区支持：作为开源生态系统的一部分，用户可以受益于社区贡献、文档和支持。

如何使用 Verodat MCP 服务器

1. 安装：首先从官方仓库下载服务器。按照文档中提供的安装说明在您的服务器环境中进行设置。
2. 配置：安装后，配置服务器设置以满足您的组织需求。这包括设置用户权限、数据存储选项以及与其他系统的集成。
3. 数据管理：使用服务器的界面上传、管理和处理您的数据。您可以创建自动化数据处理任务的工作流程。
4. 监控和维护：定期监控服务器性能并进行维护，以确保最佳运行。利用社区资源进行故障排除和更新。

常见问题解答

Verodat MCP 服务器使用了哪些编程语言构建？

Verodat MCP 服务器主要使用 [在此插入编程语言] 构建，这些语言以其性能和可扩展性而闻名。

使用 Verodat MCP 服务器是否需要费用？

不，Verodat MCP 服务器是开源的，可以免费使用。然而，您可能会产生与托管和维护相关的费用。

我可以为 Verodat MCP 服务器项目做贡献吗？

当然可以！欢迎贡献。您可以通过报告问题、提交代码或通过项目的 GitHub 仓库改善文档来参与。

我该如何获得 Verodat MCP 服务器的支持？

支持可以通过社区论坛、GitHub 问题和文档获得。您还可以与其他用户和开发人员联系以获取帮助。

Verodat MCP 服务器适合小型企业吗？

是的，Verodat MCP 服务器设计为可扩展，适合小型企业和大型企业。它的灵活性使其能够适应各种业务规模和需求。

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