civic-mcp-server

civic-mcp-server

3.3

If you are the rightful owner of civic-mcp-server and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

The CIViC MCP Server is a Cloudflare Workers-based server that facilitates querying the CIViC API, converting GraphQL responses into SQLite tables for efficient data processing.

The CIViC MCP Server is designed to provide a robust interface for querying the Clinical Interpretation of Variants in Cancer (CIViC) database. This server leverages Cloudflare Workers and Durable Objects to efficiently process and store data, enabling users to perform structured queries and data analysis on cancer genomics information. By converting GraphQL responses into queryable SQLite tables, the server allows for seamless integration with AI assistants, facilitating natural language interactions. The server is compliant with the MCP 2025-06-18 specification, ensuring structured tool output, protocol version headers, and extensive use of meta fields for additional context. While some features like OAuth 2.1 authorization and streamable HTTP transport are pending implementation, the server currently supports structured JSON data output and error handling, making it a powerful tool for researchers and clinicians working with cancer variant data.

Features

  • GraphQL to SQL Conversion: Automatically converts CIViC API responses into structured SQLite tables.
  • Efficient Data Storage: Utilizes Cloudflare Durable Objects with SQLite for data staging and querying.
  • Smart Response Handling: Optimizes performance by bypassing staging for small responses, errors, and schema introspection queries.
  • Two-Tool Pipeline: Includes 'civic_graphql_query' for executing GraphQL queries and 'civic_query_sql' for SQL-based analysis.
  • Dataset Management: Provides endpoints for listing and deleting staged datasets.

Tools

  1. civic_graphql_query

    Executes GraphQL queries against the CIViC API.

  2. civic_query_sql

    Enables SQL-based analysis of staged data.