by Verodat
Provides a Model Context Protocol server that enables AI models to interact with Verodat’s data management system, offering tool categories for consuming, designing, and managing datasets.
Enables AI models to retrieve, create, and manage datasets stored in Verodat through a standardized set of tools without writing custom API calls.
npm install && npm run build).\consume.js, design.js, or manage.js).\VERODAT_AI_API_KEY) and API endpoint (VERODAT_API_BASE_URL).\upload-dataset-rows tool.\execute-ai-query.Q: Which Node version is required?
A: Node.js v18 or higher.
Q: Do I need a Verodat account?
A: Yes, an account and an AI API key are required for authentication.
Q: Can I run only the read‑only tools?
A: Yes, use the consume.js entry point to expose the 8 consumption tools.
Q: How do I add data to an existing dataset?
A: Use the manage.js server configuration and call the upload-dataset-rows tool.
Q: Where can I find debugging tools?
A: Run npm run inspector to launch the MCP Inspector web UI.
A Model Context Protocol (MCP) server implementation for Verodat, enabling seamless integration of Verodat's data management capabilities with AI systems like Claude Desktop.
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.
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.
The server is organized into three main tool categories, each offering a progressive set of capabilities:
The base category focused on data retrieval operations:
get-accounts: Retrieve available accountsget-workspaces: List workspaces within an accountget-datasets: List datasets in a workspaceget-dataset-output: Retrieve actual data from a datasetget-dataset-targetfields: Retrieve field definitions for a datasetget-queries: Retrieve existing AI queriesget-ai-context: Get workspace context and data structureexecute-ai-query: Execute AI-powered queries on datasetsIncludes all tools from Consume, plus:
create-dataset: Create a new dataset with defined schemaIncludes all tools from Design, plus:
upload-dataset-rows: Upload data rows to existing datasetsTo install Verodat MCP Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @Verodat/verodat-mcp-server --client claude
git clone https://github.com/Verodat/verodat-mcp-server.git
cd verodat-mcp-server
npm install
npm run build
Configure Claude Desktop: Create or modify the config file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%/Claude/claude_desktop_config.jsonAdd the configuration which is mensioned below in 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"
}
}
}
}
You can configure any of the three tool categories by specifying the appropriate JS file one at a time in claude:
consume.js (8 tools for data retrieval)design.js (9 tools, includes dataset creation)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"
}
}
}
}
VERODAT_AI_API_KEY: Your Verodat API key for authenticationVERODAT_API_BASE_URL: The base URL for the Verodat API (defaults to "https://verodat.io/api/v3" if not specified)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
consume.js server configurationdesign.js server configurationmanage.js server configurationThe codebase is written in TypeScript and organized into:
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.
We welcome contributions! Please feel free to submit a Pull Request.
LICENSE file for details
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{
"mcpServers": {
"verodat-consume": {
"command": "npx",
"args": [
"-y",
"@Verodat/verodat-mcp-server"
],
"env": {
"VERODAT_AI_API_KEY": "<YOUR_API_KEY>",
"VERODAT_API_BASE_URL": "https://verodat.io/api/v3"
}
},
"verodat-design": {
"command": "npx",
"args": [
"-y",
"@Verodat/verodat-mcp-server"
],
"env": {
"VERODAT_AI_API_KEY": "<YOUR_API_KEY>",
"VERODAT_API_BASE_URL": "https://verodat.io/api/v3"
}
},
"verodat-manage": {
"command": "npx",
"args": [
"-y",
"@Verodat/verodat-mcp-server"
],
"env": {
"VERODAT_AI_API_KEY": "<YOUR_API_KEY>",
"VERODAT_API_BASE_URL": "https://verodat.io/api/v3"
}
}
}
}