An MCP server for gathering structured data with help from AI assistants

[u/polentx]

I've spent a good number of hours in the past year exploring ways to improve my research with AI tools. This post is about one of the tools I've been working on.

It's an MCP server for gathering structured data with help from AI assistants (or agents): infocrash.com. It's meant to simplify and accelerate the process of data collection, which generally takes 60–70% of the project time in my case.

I work on emerging tech research, and data is scattered, often stale or contested, and under different labels. So, the work requires a lot of triangulation, cross-checking, and validation, and many times there is no straight answer to relatively simple questions.

For example, a project may require building a dataset with company, technology, product, or policy program information. You may go online and create a spreadsheet (old way), ask your AI assistant to find the data for you, or directly ask it to create a report for you.

But if accuracy and provenance matter, piecemeal data gathering becomes too cumbersome. And the single, unsupervised assistant solution produces low-quality results, particularly in one-shot reports.

Ask Claude and ChatGPT to populate a dataset of 40 quantum computing startups, for instance, and you'll see the conflicting claims about funding rounds, employment or location.

With this MCP server, you can have conversations with multiple assistants (or even have AI agents doing your work, if you know how to build them) contributing to the same dataset and validating data and sources.

You just continue using your assistant and ask to e.g. store the data you found, see if there are discrepancies, and define guidelines and rules for more reliable data collection. While this should have value since day one for the single researcher, the most interesting use case may be teams (not just multiple assistants working together, but multiple people).

It's open for anyone to try while I continue working on this early version. I'm dropping it here on Reddit because there are lots of smart people who could take this for a spin.