Skip to main content
Glama

list_all_attributes

Retrieve a filtered list of all attributes for a specified dataset in Biomart MCP, excluding less common attributes like homologs and microarray probes, returned in CSV format. Use to explore dataset characteristics efficiently.

Instructions

Lists all available attributes for a given dataset with some filtering. This function returns a filtered list of all attributes available for the specified dataset. Some less commonly used attributes (homologs, microarray probes) are filtered out to reduce the response size. CAUTION: This function can return a large number of attributes and may be unstable for certain datasets. Consider using list_common_attributes first. Args: mart (str): The mart identifier (e.g., "ENSEMBL_MART_ENSEMBL") dataset (str): The dataset identifier (e.g., "hsapiens_gene_ensembl") Returns: str: CSV-formatted table of all filtered attributes. Example: list_all_attributes("ENSEMBL_MART_ENSEMBL", "hsapiens_gene_ensembl")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetYes
martYes

Implementation Reference

  • The handler function for the 'list_all_attributes' MCP tool. Decorated with @mcp.tool() for automatic registration and schema inference from type hints and docstring. Lists filtered attributes for a Biomart dataset and returns as CSV.
    @mcp.tool() def list_all_attributes(mart: str, dataset: str): """ Lists all available attributes for a given dataset with some filtering. This function returns a filtered list of all attributes available for the specified dataset. Some less commonly used attributes (homologs, microarray probes) are filtered out to reduce the response size. CAUTION: This function can return a large number of attributes and may be unstable for certain datasets. Consider using list_common_attributes first. Args: mart (str): The mart identifier (e.g., "ENSEMBL_MART_ENSEMBL") dataset (str): The dataset identifier (e.g., "hsapiens_gene_ensembl") Returns: str: CSV-formatted table of all filtered attributes. Example: list_all_attributes("ENSEMBL_MART_ENSEMBL", "hsapiens_gene_ensembl") """ server = pybiomart.Server(host=DEFAULT_HOST) df = server[mart][dataset].list_attributes() df = df[~df["name"].str.contains("_homolog_", na=False)] df = df[~df["name"].str.contains("dbass", na=False)] df = df[~df["name"].str.contains("affy_", na=False)] df = df[~df["name"].str.contains("agilent_", na=False)] return df.to_csv(index=False).replace("\r", "")

Other Tools

Related Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jzinno/biomart-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server