What is Verodat MCP Server

Verodat MCP Server is an implementation of the Model Context Protocol (MCP) designed for Verodat, allowing AI systems to connect with Verodat’s data management services. It establishes a standardized interface for data access and manipulation, supporting various operations categorized under data consumption, design, and management.

Use cases

The primary use cases include retrieving data from Verodat, creating and modifying datasets, executing AI queries on data, and managing workspaces. This server facilitates seamless integration with AI platforms, enabling users to harness Verodat’s data capabilities for enhanced decision-making and analytics.

How to use

To use the Verodat MCP Server, users need to install it via Node.js, configure their Claude Desktop environment with the necessary API credentials, and specify the desired tool category for operations. Commands are then executed through the configured environment, allowing for interaction with datasets according to the selected capabilities.

Key features

Key features include a modular approach with three tool categories: Consume for data retrieval, Design for dataset creation, and Manage for data uploads. Additionally, it supports authentication via API keys and provides easy configuration options for the AI model’s environment.

Where to use

The Verodat MCP Server is used primarily in data-driven AI applications, especially where integration with Verodat’s robust data management services is needed. It is ideal for organizations looking to enhance their AI models with structured data workflows and deepen their analytical capabilities using datasets.

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