Verodat Mcp Server

What is Verodat MCP Server?

Verodat MCP Server is an open-source project designed to provide a robust and scalable server solution for managing and processing data. It is particularly useful for organizations looking to implement a centralized data management system that can handle various data types and workflows efficiently. The server is built with a focus on performance, reliability, and ease of integration with existing systems.

Features of Verodat MCP Server

• Scalability: The server can handle increasing amounts of data and user requests without compromising performance.
• Data Management: It offers comprehensive tools for data storage, retrieval, and processing, making it ideal for businesses that rely on data-driven decision-making.
• Open Source: Being an open-source project, it allows developers to customize and extend its functionalities according to their specific needs.
• User-Friendly Interface: The server comes with an intuitive interface that simplifies the management of data and server settings.
• Community Support: As part of the open-source ecosystem, users can benefit from community contributions, documentation, and support.

How to Use Verodat MCP Server

1. Installation: Begin by downloading the server from the official repository. Follow the installation instructions provided in the documentation to set it up on your server environment.
2. Configuration: After installation, configure the server settings to suit your organizational needs. This includes setting up user permissions, data storage options, and integration with other systems.
3. Data Management: Use the server's interface to upload, manage, and process your data. You can create workflows that automate data handling tasks.
4. Monitoring and Maintenance: Regularly monitor server performance and conduct maintenance to ensure optimal operation. Utilize community resources for troubleshooting and updates.

Frequently Asked Questions

What programming languages is Verodat MCP Server built with?

Verodat MCP Server is primarily built using [insert programming languages here], which are known for their performance and scalability.

Is there a cost associated with using Verodat MCP Server?

No, Verodat MCP Server is open-source and free to use. However, you may incur costs related to hosting and maintenance.

Can I contribute to the Verodat MCP Server project?

Absolutely! Contributions are welcome. You can participate by reporting issues, submitting code, or improving documentation through the project's GitHub repository.

How can I get support for Verodat MCP Server?

Support is available through community forums, GitHub issues, and documentation. You can also connect with other users and developers for assistance.

Is Verodat MCP Server suitable for small businesses?

Yes, Verodat MCP Server is designed to be scalable, making it suitable for both small businesses and large enterprises. Its flexibility allows it to adapt to various business sizes and needs.

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