TestGen MCP Cheat Sheet: 96 Tools, One Page, Zero Excuses

TestGen 5.70.2 completes the Model Context Protocol server. That's 96 tools covering the whole data quality loop, callable from Claude, Cursor, Copilot, or the agent you're building. Grab the one-page cheat sheet.

Written by Chris Bergh on July 6, 2026

Data QualityDataOps TestGenOpen Source
TestGen MCP Cheat Sheet: 96 Tools, One Page, Zero Excuses

Your AI assistant can now run your data quality program: the TestGen MCP server is complete

You have an AI assistant that can write a sonnet about your sales pipeline. It cannot tell you whether the sales table loaded this morning. That gap closed on June 30.

TestGen 5.70.2 completes our Model Context Protocol server. Every workflow in TestGen is now callable by any MCP client: Claude, Claude Code, Cursor, Copilot, or the agent you’re building yourself. That’s 96 tools covering the whole data quality loop, from “what data do I have” to “email me when the score drops.”

What shipped

Earlier releases gave the MCP server profiling, test definitions, hygiene issues, runs, scores, schedules, and notifications. The June 30 release added the setup and management layer that completes the loop. Your assistant can now create and update table groups and test suites, view and test database connections, and manage monitors end-to-end. It can set test-result dispositions in bulk, move test definitions between suites, and edit Data Catalog metadata.

You no longer need the TestGen UI open to run TestGen. You need a chat window.

What a conversation looks like

We connected Claude to a TestGen instance and asked one question: “What data do I have and how healthy is it?” Thirty seconds later, we had the full inventory and a quality score of 78.9 on a table group we’d been ignoring.

The follow-up questions did the work that used to take a morning. “What’s dragging the score?” surfaced 30 hygiene issues, none of which anyone had tested for. One table had loaded every column as varchar(65535). The prices were 96% numeric, the dates were 97% dates, and the remaining 3% were strings like ERROR and UNKNOWN hidden in numeric columns. “Show me the rows behind that” pulled the actual offending records from the source database, not a chart about them.

The finding that made us wince: the cleaned table still carried names, emails, zip codes, and income, all flagged as PII. Someone fixed the values and forgot the identifiers. The “clean” table was a compliance problem, and a five-word question found it.

Then: “Generate tests and run them.” The tests wrote themselves from the profile. Twelve failures came back, and they matched the hygiene story. “Dismiss the recency issue; it’s historical data. Confirm the rest.” Every disposition landed in TestGen with an audit trail. Blind to trusted, one conversation.

The whole surface on one page

Ninety-six tools is a lot to hold in your head, so we made a cheat sheet. One page. Every tool, grouped by the eight stages of the loop: discover, profile, hygiene, test, run, monitor, score, operate. Connection instructions in the corner, starter prompts at the bottom.

TestGen MCP cheat sheet: 96 tools grouped into the eight stages of the data quality loop, with connection instructions and starter prompts

One detail we’re proud of: the orange dots. Every tool that writes to your TestGen instance carries one. Everything else is read-only. When your security team asks what the AI can actually touch, hand them the page and point at the dots. The read/write boundary is visible before anyone clicks “always allow.”

Why MCP and not another chatbot

TestGen has no built-in chat window, on purpose. MCP is a standard, so your assistant of choice uses TestGen as a tool, right next to your Jira and your warehouse.

Permissions hold. The MCP server authenticates as you, and every tool runs with your TestGen role. An analyst’s assistant can read scores; it cannot delete scorecards.

The audit trail survives. Dispositions, test notes, and run history are captured in TestGen in the same way as in the UI. The agent leaves footprints your governance team can follow.

And it composes. Test suites can push results straight into DataOps Observability. Hosted platforms like Databricks Genie can call the same server. The tools you use in a chat today are the tools your autonomous data quality agent uses tomorrow. We’re building that agent too, and this MCP server is its hands.

Get started in five minutes

Point your MCP client at https://<your-testgen-host>/mcp. Modern clients handle sign-in via OAuth in your browser; provide them with the URL and have them approve the connection. Then ask: “List the projects I have access to in TestGen.” If you get your projects back, you’re live. The setup guide covers personal access tokens and hosted platforms.

TestGen is open source under the Apache 2.0 license, and so is the MCP server. No SKU, no per-seat agent tax. Install TestGen, connect your database, connect your assistant, and ask it what’s wrong with your data. It will tell you. That’s the uncomfortable part.

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Chris Bergh

Chris Bergh

CEO and Head Chef at DataKitchen. He is a leader of the DataOps movement and is the co-author of the DataOps Cookbook and the DataOps Manifesto.

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