Asset Details
Do you wish to reserve the book?
CIViC MCP: Integrating Large Language Models with the Clinical Interpretations of Variants in Cancer
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
CIViC MCP: Integrating Large Language Models with the Clinical Interpretations of Variants in Cancer
Do you wish to request the book?
CIViC MCP: Integrating Large Language Models with the Clinical Interpretations of Variants in Cancer
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
CIViC MCP: Integrating Large Language Models with the Clinical Interpretations of Variants in Cancer
2025
Overview
The Clinical Interpretation of Variants in Cancer (CIViC) knowledgebase provides a community-driven, open-source platform for discussing the biological and Clinical Significance of molecular variants in cancer. To enable users to make complex connections between CIViC information, we developed the CIViC Model Context Protocol (MCP) server, which allows large language models (LLMs) to directly interface with the CIViC API through natural language, facilitating the rapid summarization of expertly curated cancer variant interpretations.
The CIViC MCP server is detailed at https://github.com/griffithlab/civic-mcp-server with archived code and evaluation data deposited in Zenodo (DOI: 10.5281/zenodo.17344050). The repository is a fork of https://github.com/QuentinCody/civic-mcp-server (QuentinCody 2025) and includes instructions for accessing the server through the Claude desktop app and hosting it locally with GPT-5. We also provide a Python script for directly querying the MCP server.
Supplementary data are available at
online.
Publisher
Cold Spring Harbor Laboratory,Cold Spring Harbor Laboratory Preprints
Subject
