# Services

- [MPContribs](/services/mpcontribs.md): Introduction to MP's contribution platform MPContribs
- [ML & AI applications](/services/ml-and-ai-applications.md): This section summarizes the ways in which Materials Project and its collaborators' data and tools can help with the development of new ML methods.
- [MatBench](/services/ml-and-ai-applications/matbench.md): Tools for assessing the ability of machine learning models to predict materials properties, similar to ML community standards like ImageNet
- [Matbench Discovery](/services/ml-and-ai-applications/matbench-discovery.md): With Janosh Riebesell of Alpha Lee's and Kristin Persson's groups
- [MPtrj](/services/ml-and-ai-applications/mptrj.md)
- [r2SCAN datasets](/services/ml-and-ai-applications/matpes.md): Development of robust, high fidelity datasets for training universal machine learning interatomic potentials
- [MP + LLMs (MCP)](/services/ml-and-ai-applications/mcp.md): Model context protocols for integrating Materials Project data with large lanuage models.