jzinno biomart mcp

WHAT IT CONNECTS

jzinno biomart mcp 为 AI Agent 提供什么

• **Mart and Dataset Discovery**: List available marts and datasets to explore the Biomart database structure
• **Attribute and Filter Exploration**: View common or all available attributes and filters for specific datasets
• **Data Retrieval**: Query Biomart with specific attributes and filters to get biological data
• **ID Translation**: Convert between different biological identifiers (e.g., gene symbols to Ensembl IDs)
• We are only using `@mcp.tool()` here by design, this is to maximize compatibility with clients that support MCP as seen in the [docs](https://modelcontextprotocol.io/clients).
• We are using `@lru_cache` to cache results of functions that are computationally expensive or make external API calls.
• We need to be mindful to not blow up the context window of the model, for example you'll see `df.to_csv(index=False).replace("\r", "")` in many places. This csv style return is much more token efficient than something like `df.to_string()` where the majority of the tokens are whitespace. Also be mindful of the fact that pulling all genes from a chromosome or similar large request will also be too large for the context window.
• Add webscraping for resource sites with `bs4`, for example we got the Ensembl gene ID for NOTCH1 then maybe in some cases it would be usful to grap the collated `Comments and Description Text from UniProtKB` section from [it's page on UCSC](https://genome.ucsc.edu/cgi-bin/hgGene?db=hg38&hgg_chrom=chr9&hgg_gene=ENST00000651671.1&hgg_start=136494433&hgg_end=136546048&hgg_type=knownGene)
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