AcademyMCP serversData and reporting

Dingo

Data and AI teams that need to check the quality of training or evaluation data before using it.

  • Recommendedour rating
  • 757gitHub stars
  • Apache-2.0licence
  • 2 days agolast update
git clone https://github.com/MigoXLab/dingo.git
README.md

Loading the file...

What it does

A data quality evaluation tool for AI datasets, with an MCP server. Through MCP you can run rule-based and LLM-based evaluations and list the available rules and prompts. Dingo is a Python package that also covers checks such as hallucination detection and RAG evaluation.

Use cases

  1. 01Run a rule-based quality check on a dataset
  2. 02Evaluate samples with an LLM-based prompt
  3. 03List the available rules and prompts before a run

Questions about
Dingo.

What is Dingo used for?

Data and AI teams that need to check the quality of training or evaluation data before using it. A data quality evaluation tool for AI datasets, with an MCP server. Through MCP you can run rule-based and LLM-based evaluations and list the available rules and prompts. Dingo is a Python package that also covers checks such as hallucination detection and RAG evaluation.

How do I install Dingo?

Run this in your terminal: git clone https://github.com/MigoXLab/dingo.git

Is Dingo open source?

Yes. The code is on GitHub (MigoXLab/dingo) under the Apache-2.0 licence.

Is Dingo safe to use?

It passed our automatic scan for credential theft, hidden instructions and risky install commands. Third party open source software. Sabemos AI does not maintain it. Check the code and permissions before you connect it to company data.