Verodat MCP Server

What is Verodat MCP Server about?

Provides a Model Context Protocol (MCP) server that exposes Verodat's data handling functions—such as listing accounts, workspaces, datasets, and executing AI‑powered queries—to AI models. The server is organized into three tool categories (Consume, Design, Manage) that progressively add write capabilities.

How to use Verodat MCP Server?

1. Install the package (recommended via Smithery):

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

2. Configure Claude Desktop (or another AI client) with a JSON entry that points to the desired tool set (consume.js, design.js, or manage.js).
3. Set environment variables for authentication (VERODAT_AI_API_KEY) and optionally override the API base URL (VERODAT_API_BASE_URL).
4. Run the server via the configured command; the AI model will communicate over stdio using the defined MCP commands.

Key features of Verodat MCP Server

• Three tool categories:
  • Consume – 8 read‑only tools (accounts, workspaces, datasets, queries, etc.).
  • Design – adds dataset creation.
  • Manage – adds row upload for full data lifecycle management.
• TypeScript codebase with Zod validation for robust request handling.
• MCP Inspector for debugging communication over stdio.
• Easy installation via Smithery or manual npm install and build.
• Environment‑driven configuration allowing seamless switching between Verodat instances.

Use cases of Verodat MCP Server

• AI‑assisted data analysis: Retrieve dataset outputs and run AI queries directly from Claude Desktop.
• Automated dataset provisioning: Create new datasets on the fly as part of AI‑driven workflows.
• Bulk data ingestion: Upload rows to existing datasets after AI‑generated transformations.
• Multi‑workspace reporting: Pull accounts, workspaces, and dataset metadata for cross‑project insights.

FAQ from Verodat MCP Server

Q: Which tool set should I use? A: Choose consume.js for read‑only operations, design.js when you need to create datasets, and manage.js for full upload capabilities.

Q: Do I need a Verodat account? A: Yes—sign up at verodat.com and generate an AI API key from the dashboard.

Q: How do I change the API endpoint? A: Set the VERODAT_API_BASE_URL environment variable; it defaults to https://verodat.io/api/v3.

Q: Can I debug the MCP communication? A: Run npm run inspector to launch the MCP Inspector web UI.

Q: Is the server compatible with other AI models? A: While the README focuses on Claude Desktop, any model that supports MCP over stdio can use the server.

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

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