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Integrum - Reflection based MCP Server from any Python module or library Yesterday I open sourced Integrum, a library that is a part of AlphaDeep world. It allows you to quickly create MCP server(s) from existing Python libraries or modules (or even plain classes!). It is released with MIT license and I hope somebody else also finds it useful for a more formal approach to giving agents additional capabilities (compared to just letting them writing arbitrary code with or without a sandbox).

Couple of interesting things about it:

State Management #

Obviously not all Python code is functional, so some state management is required. I opted for a simple in memory object store pattern with keys being “model-friendly” -> they are words to save tokens. Also there is tuple unpacking, array access and other simple needed things to get started.

Multi-user isolation #

LLM sessions are stateless by design so I thought it would be hard to keep track of which object belongs to which user. Luckily after inspecting FastMCP implementation it seems like context is present (for HTTP/SSE anyway) so that didn’t turn out to be that difficult in the end.

Gemma experiment (recursive self-improvement? :)) # #

To test Integrum out I gave Gemma 4 (26B A4B) access to scikit-learn Random Forest Classifier and a toy dataset (Iris). Without much trouble Gemma was able to build and evaluate a small model. It didn’t experiment with hyperparameter tuning but since it got 100% validation accuracy it didn’t have the opportunity.

It would be interesting to see what it would do with a “hard” problem. It would also be interesing if we gave it tools to update its own weights to improve performance on some benchmark. :)