We are going to implement an MCP server to orchestrate the Synthetic Data Vault (SDV) for completely local synthetic data generation. Agents will be able to connect to discover tools and then create, statistically evaluate, and visualize synthetic datasets based on our real-world tabular data.
We use:
- SDV for synthetic data generation of tabular data
- Cursor (MCP Host)
Run these commands in project root
uv syncRun the MCP server with the created configuration file as mcp.json either globally or in the current project directory. Here's the code of configuring MCP globally to run the server:
{
"mcpServers": {
"sdv_mcp": {
"command": "uv",
"args": [
"--directory",
"/Users/akshay/Eigen/ai-engineering-hub/sdv-mcp",
"run",
"--with",
"mcp",
"server.py"
]
}
}
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Contributions are welcome! Feel free to fork this repository and submit pull requests with your improvements.
