Great Expectations Data Quality Server

by davidf9999 · devops · mcp-server, smithery

Expose Great Expectations data-quality checks as callable tools for LLM agents. Load datasets, define validation rules, and run data quality checks programmatically to integrate robust data validation into automated workflows. Support multiple data sources, authentication methods, and transport modes for flexible deployment.

Source: https://smithery.ai/servers/davidf9999/gx-mcp-server

Install

git clone https://smithery.ai/servers/davidf9999/gx-mcp-server

Tags: mcp-server, smithery

Source: smithery

About devops MCP servers and Claude skills

devops MCP servers extend what AI agents can do inside Claude Code, Cursor, Copilot, Codex, and Windsurf. The Skiln directory indexes 16,000+ such integrations across 22 categories.

Great Expectations Data Quality Server is one of hundreds of devops entries indexed on Skiln. Browse the full devops category or the complete directory of Claude skills, MCP servers, agents, commands, and hooks.

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Frequently asked questions

How do I install Great Expectations Data Quality Server?

Add the install command above to your Claude Code, Cursor, or Windsurf MCP configuration. Most servers register via npx, a local command, or a Docker image. Refer to the source repository for environment variables and credential requirements.

Which clients support Great Expectations Data Quality Server?

Any MCP-compatible client works: Claude Desktop, Claude Code CLI, Cursor, Windsurf, Zed, and VS Code with the official MCP extension. OpenAI Codex and GitHub Copilot increasingly support MCP via adapter bridges.

Is Great Expectations Data Quality Server free?

The server itself is typically open source. Any upstream service (API keys, paid tiers, hosted infrastructure) may have its own pricing. Check the source repository for details.