Biomart

A MCP server to interface with Biomart

python

7

GitHub Stars

python

Language

6 months ago

First Indexed

2 months ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "jzinno-biomart-mcp": {
      "command": "mcp",
      "args": [
        "dev",
        "biomart-mcp.py"
      ]
    }
  }
}

Biomart MCP provides an MCP server that lets large language models access Biomart data by querying marts, datasets, attributes, and IDs through the Model Context Protocol. You can discover Biomart structures, retrieve data, and translate identifiers in a streamlined, MCP-friendly way.

How to use

You run the Biomart MCP server alongside your MCP client to access Biomart databases from your LLM workflows. Start the server in development mode, then issue MCP requests from your client to explore Mart/Dataset structures, fetch attributes and filters, retrieve data, and translate identifiers.

How to install

Prerequisites: you should have a working MCP client setup and a compatible runtime environment for the Biomart MCP server. The server can be started using the MCP command shown below.

uv venv

# MacOS/Linux
source .venv/bin/activate

# Windows
.venv\Scripts\activate

uv sync #or uv add mcp[cli] pybiomart

# Run the server in dev mode
mcp dev biomart-mcp.py

Additional setup notes

If you are using Claude Desktop or other MCP-enabled clients, you can install Biomart MCP via different workflows shown in the commands below. The CLI-based development start command is the intended runtime you will use to connect your MCP client to Biomart.

Tools and endpoints

Biomart MCP exposes a set of practical capabilities you can invoke from your MCP client:

Mart and Dataset Discovery: List available marts and datasets to explore Biomart’s structure.
Attribute and Filter Exploration: View common or all attributes and filters for specific datasets.
Data Retrieval: Query Biomart with chosen attributes and filters to obtain biological data.
ID Translation: Convert between different biological identifiers (e.g., gene symbols to Ensembl IDs).

Available tools

MartDiscovery

Discover available Biomart marts and their datasets to understand the database structure.

DatasetDiscovery

List datasets within a selected Biomart mart to identify usable data collections.

AttributeDiscovery

Explore available attributes and filters for a given dataset to construct queries.

DataRetrieval

Retrieve data by querying Biomart with selected attributes and filters.

IDTranslation

Translate biological identifiers between formats (e.g., gene symbols to Ensembl IDs).