EnrichMCP exposes a Python framework for building data-driven MCP servers. It provides tools to transform data models into semantic layers for AI agents. The server connects to data sources and integrates with Featureform for feature management. Developers use it to create custom data enrichment services for AI applications.
EnrichMCP exposes a Python framework for building data-driven MCP servers. It provides tools to transform data models into semantic layers for AI agents. The server connects to data sources and integrates with Featureform for feature management. Developers use it to create custom data enrichment services for AI applications.
pip install enrichmcpAdd this configuration to your claude_desktop_config.json:
{
"mcpServers": {
"featureform-enrichmcp-github": {
"command": "uvx",
"args": [
"pip install enrichmcp"
]
}
}
}Restart Claude Desktop, then ask:
"What tools do you have available from enrichmcp?"
No configuration required. This server works out of the box.
"What resources are available in enrichmcp?"
Claude will query available resources and return a list of what you can access.
"Show me details about [specific item] in enrichmcp"
Claude will fetch and display detailed information about the requested item.
"Create a new [item] in enrichmcp with [details]"
Claude will use the appropriate tool to create the resource and confirm success.
We build custom MCP integrations for B2B companies. From simple connections to complex multi-tool setups.