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Annotate scRNA-seq cell types and manage CellTypist models with natural language.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "CellTypist MCP" yet — see the docs or source repo.
List the currently available CellTypist models and briefly describe the annotation scenarios they are suitable for.
A list of available models with short usage notes to help choose an annotation model.
Download an appropriate CellTypist model and annotate cell types for this scRNA-seq dataset, returning predicted labels for each cell or cluster.
The tool downloads the model and returns predicted cell type labels.
Train a custom CellTypist model from this labeled single-cell dataset and explain what annotation tasks the trained model can support.
Information about the trained custom model and the types of annotation tasks it can be used for.
Researchers working with scRNA-seq data can use CellTypist models to automatically annotate cell types, reducing manual marker-gene comparison. This is useful for initial analysis and result preparation.
Data analysts can list and download available models first, then choose the most suitable CellTypist model for annotation. This makes it easier to switch models across datasets.
When existing models do not fully cover the target samples, researchers can train a custom model from labeled data for cell type annotation in specific tissues or experimental conditions.
It is an MCP tool for automated cell type annotation in scRNA-seq analysis using CellTypist models. It also supports listing, downloading, and training models through natural-language requests.
Based on the provided description, it supports listing models, downloading models, training models, and annotating cell types. These capabilities focus on using and managing CellTypist models.
The provided material does not include installation steps, runtime details, or prerequisite requirements. See the source repository for specifics.
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