# verodat-mcp-server

> MCP Server

The Verodat MCP Server repository provides a Model Context Protocol implementation for integrating Verodat's data management with AI systems like Claude Desktop, enabling account, workspace, and dataset operations.

## Overview

- **Category:** AI
- **Language:** TypeScript
- **Stars:** 3
- **Forks:** 0
- **Owner:** Verodat
- **GitHub:** https://github.com/Verodat/verodat-mcp-server
- **Created:** 2025-01-30T13:15:33+00:00
- **Updated:** 2025-03-27T07:14:48+00:00
- **Source:** https://model-context-protocol.com/servers/verodat-mcp-server-model-context-protocol

## Setup

## Setup

**Installing via Smithery:**

To install Verodat MCP Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@Verodat/verodat-mcp-server):

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

**Manual Installation:**
1. Clone the repository:
   ```bash
   git clone https://github.com/Verodat/verodat-mcp-server.git
   cd verodat-mcp-server
   ```

2. Install dependencies and build:
   ```bash
   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 following configuration:
   ```json
   {
       "mcpServers": {
           "verodat": {
               "command": "node",
               "args": ["path/to/verodat-mcp-server/build/src/index.js"],
               "env": {
                   "VERODAT_AI_API_KEY": "your-verodat-ai-api-key"
               }
           }
       }
   }
   ```

**Getting Started with Verodat:**

1. Sign up for a Verodat account at [verodat.com](https://verodat.com)
2. Generate an AI API key from your Verodat dashboard
3. Add the API key to your Claude Desktop configuration

## Tools

## Available Tools

1. Account & Workspace Management (List accessible accounts and browse workspaces within accounts).
2. Dataset Operations (Create, query, filter, and retrieve dataset records).
3. AI Integration (Fetch workspace context for AI processing and execute AI-powered queries on datasets).
4. MCP commands (Provides commands for account, workspace, dataset, and AI operations).
5. MCP Inspector tool (Provides debugging tools via a browser URL).