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    Verodat Mcp Server

    Verodat MCP Server Implementation

    3 stars
    TypeScript
    Updated Sep 6, 2025

    Table of Contents

    • Overview
    • Overview
    • Tool Categories
    • 1. Consume (8 tools)
    • 2. Design (9 tools)
    • 3. Manage (10 tools)
    • Prerequisites
    • Installation
    • Quick Start
    • Installing via Smithery
    • Manual Installation
    • Getting Started with Verodat
    • Configuration
    • Configuration Options
    • Environment Variables
    • Tool Usage Guide
    • Available Commands
    • Selecting the Right Tool Category
    • Security Considerations
    • Development
    • Debugging
    • Contributing
    • License
    • Support

    Table of Contents

    • Overview
    • Overview
    • Tool Categories
    • 1. Consume (8 tools)
    • 2. Design (9 tools)
    • 3. Manage (10 tools)
    • Prerequisites
    • Installation
    • Quick Start
    • Installing via Smithery
    • Manual Installation
    • Getting Started with Verodat
    • Configuration
    • Configuration Options
    • Environment Variables
    • Tool Usage Guide
    • Available Commands
    • Selecting the Right Tool Category
    • Security Considerations
    • Development
    • Debugging
    • Contributing
    • License
    • Support

    Documentation

    MseeP.ai Security Assessment Badge

    Verodat MCP Server

    MCP

    smithery badge

    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.

    image

    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:

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

    Manual Installation

    1. Clone the repository:

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

    2. Install dependencies and build:

    code
    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:

    json
    {
      "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:

    json
    {
      "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:

    code
    // 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:

    code
    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

    ---

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