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Expose Great Expectations data-quality checks as MCP tools for LLM agents.
](https://pypi.org/project/gx-mcp-server) [ ](https://hub.docker.com/r/davidf9999/gx-mcp-server) [ ](https://github.com/davidf9999/gx-mcp-server/actions/workflows/ci.yaml) [
- Motivation
- Quick Start
- Features
- Installation & Usage
- MCP Client Configuration
- Authentication
- Docker
- Configuration
- Development
- Security
- License & Contributing
Large Language Model (LLM) agents often need to interact with and validate data. Great Expectations is a powerful open-source tool for data quality, but it's not natively accessible to LLM agents. This server bridges that gap by exposing core Great Expectations functionality through the Model Context Protocol (MCP), allowing agents to:
Works with Claude (desktop and mobile), Cursor, Windsurf, VS Code, and any MCP-compatible AI app.
Category: Developer Tools
Don't lose this
Three weeks from now, you'll want gx-mcp-server again. Will you remember where to find it?
Save it to your library and the next time you need gx-mcp-server, it’s one tap away — from any AI app you use. Group it into a bench with the rest of the team for that kind of task and you can pull the whole stack at once.
⚡ Pro tip for geeks: add a-gnt 🤵🏻♂️ as a custom connector in Claude or a custom GPT in ChatGPT — one click and your library is right there in the chat. Or, if you’re in an editor, install the a-gnt MCP server and say “use my [bench name]” in Claude Code, Cursor, VS Code, or Windsurf.
a-gnt's Take
Our honest review
This plugs directly into your AI and gives it new abilities it didn't have before. gx-mcp-server. Once connected, just ask your AI to use it. It's completely free and works across most major AI apps. This one just landed in the catalog — worth trying while it's fresh.
Tips for getting started
Tap "Get" above, pick your AI app, and follow the steps. Most installs take under 30 seconds.
What's New
Imported from awesome:wong2/awesome-mcp-servers
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