Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@anndata-mcp show me the summary of the AnnData object at /data/sample.h5ad"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Allows to retrieve information about an AnnData object via MCP using the read_lazy function from anndata.
Please refer to the documentation, in particular, the API documentation.
You can also find the project on BioContextAI, the community-hub for biomedical MCP servers: anndata-mcp on BioContextAI.
Related MCP server: Scanpy-MCP
You need to have Python 3.11 or newer installed on your system. If you don't have Python installed, we recommend installing uv.
There are several alternative options to install anndata-mcp:
Use uvx to run it immediately:
uvx anndata-mcpInclude it in one of various clients that supports the mcp.json standard, please use:
{
"mcpServers": {
"anndata-mcp": {
"command": "uvx",
"args": ["anndata-mcp"]
}
}
}Install it through pip:
pip install --user anndata-mcpInstall the latest development version:
pip install git+https://github.com/biocontext-ai/anndata-mcp.git@mainIf you found a bug, please use the issue tracker.
If this MCP server is useful to your research, please cite the BioContextAI and the anndata publications:
@article{BioContext_AI_Kuehl_Schaub_2025,
title={BioContextAI is a community hub for agentic biomedical systems},
url={http://dx.doi.org/10.1038/s41587-025-02900-9},
urldate = {2025-11-06},
doi={10.1038/s41587-025-02900-9},
year = {2025},
month = nov,
journal={Nature Biotechnology},
publisher={Springer Science and Business Media LLC},
author={Kuehl, Malte and Schaub, Darius P. and Carli, Francesco and Heumos, Lukas and Hellmig, Malte and Fernández-Zapata, Camila and Kaiser, Nico and Schaul, Jonathan and Kulaga, Anton and Usanov, Nikolay and Koutrouli, Mikaela and Ergen, Can and Palla, Giovanni and Krebs, Christian F. and Panzer, Ulf and Bonn, Stefan and Lobentanzer, Sebastian and Saez-Rodriguez, Julio and Puelles, Victor G.},
year={2025},
month=nov,
language={en},
}@article{Virshup2024,
title = {anndata: Access and store annotated data
matrices},
volume = {9},
ISSN = {2475-9066},
url = {http://dx.doi.org/10.21105/joss.04371},
DOI = {10.21105/joss.04371},
number = {101},
journal = {Journal of Open Source Software},
publisher = {The Open Journal},
author = {Virshup, Isaac and Rybakov, Sergei and Theis, Fabian J. and Angerer, Philipp and Wolf, F. Alexander},
year = {2024},
month = sep,
pages = {4371}
}Provide basic descriptive statistics (e.g., count, mean, std, min, max, etc. or value counts) for an attribute or attribute value of an optionally filtered AnnData object.
Inputs: path (required), attribute (required), key, filter_value, +5 more. Returns: error, description, value_counts
Get a summary of an AnnData object from a file or URL.
Inputs: path (required). Returns: error, n_obs, X_type, layers, +10 more
View the raw data of an AnnData object.
Inputs: path (required), attribute (required), key, filter_value, +7 more. Returns: data, error, data_type, full_shape, +1 more
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 3 tools
The three tools have distinct purposes: view_raw_data displays raw data, get_summary provides a structural overview, and get_descriptive_stats computes statistical summaries. While summary and stats could overlap slightly, their focus on structure vs. attribute-level statistics keeps them distinguishable.
All tool names follow a consistent verb_noun pattern using 'view_' or 'get_' prefixes, making the naming predictable and easy to understand.
With only 3 tools, the server is on the thin side but appropriate for a focused read-only inspection toolset. It is not too sparse to be useless, but it offers limited functionality.
The server is missing common AnnData operations such as listing attributes, accessing subsets, or modifying/saving data. This creates significant gaps for users expecting a more complete workflow, though basic inspection is covered.
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