Primekg MCP
A project to import the Precision Medicine Knowledge Graph (PrimeKG) into the Neo4j database for biomedical data analysis and exploration.
rating : 2 points
downloads : 6.4K
What is PrimeKG to Neo4j?
This is a project to import the Precision Medicine Knowledge Graph (PrimeKG) data into the Neo4j graph database. PrimeKG integrates 20 high-quality biomedical resources, describing 17,080 diseases and more than 4 million relationships.How to use PrimeKG to Neo4j?
The project provides a complete processing workflow: 1) Download and process PrimeKG data. 2) Import it into the Neo4j database. 3) Provide query and analysis tools.Use cases
Suitable for biomedical researchers, drug developers, and data scientists to conduct disease association analysis, drug discovery, and precision medicine research.Main features
Multi-source data integration
Integrate 20 high-quality biomedical resources to achieve cross-resource data association.
Graphical display
Provide an intuitive graphical interface through Neo4j to display the complex relationships between entities such as diseases, genes, and drugs.
Flexible query and analysis
Support the Cypher query language and perform complex relationship path analysis and pattern matching.
Advantages
Integrate multiple authoritative biomedical databases with high data quality.
The graph database structure is suitable for displaying complex biological network relationships.
Provide a standardized data import process and query interface.
Limitations
Basic knowledge of Neo4j and Cypher is required to make full use of it.
The data volume is large, requiring sufficient storage and computing resources.
Regular updates require re - importing the complete data set.
How to use
Prepare the environment
Install Docker and the Neo4j database (version 4.4 or higher is recommended).
Download PrimeKG data
Download the latest PrimeKG data set from the project website.
Data preprocessing
Run the preprocessing script to prepare the data for import.
Import into Neo4j
Use the provided import tool to import the processed data into Neo4j.
Usage examples
Disease - drug association analysis
Explore all drugs related to a specific disease and their mechanisms of action.
Multi - hop relationship path discovery
Discover the potential associations between diseases through intermediate entities such as genes and pathways.
Frequently Asked Questions
How much storage space is required to store PrimeKG data?
What is the data update frequency?
Can I use this project without Neo4j experience?
Related resources
PrimeKG official website
The official website of the PrimeKG project, including data download and documentation.
Neo4j Learning Center
Official Neo4j learning resources, including Cypher language tutorials.
Project GitHub repository
The source code and issue tracking of this project.

Gitlab MCP Server
Certified
The GitLab MCP server is a project based on the Model Context Protocol that provides a comprehensive toolset for interacting with GitLab accounts, including code review, merge request management, CI/CD configuration, and other functions.
TypeScript
16.6K
4.3 points

Notion Api MCP
Certified
A Python-based MCP Server that provides advanced to-do list management and content organization functions through the Notion API, enabling seamless integration between AI models and Notion.
Python
14.8K
4.5 points

Duckduckgo MCP Server
Certified
The DuckDuckGo Search MCP Server provides web search and content scraping services for LLMs such as Claude.
Python
44.0K
4.3 points

Markdownify MCP
Markdownify is a multi-functional file conversion service that supports converting multiple formats such as PDFs, images, audio, and web page content into Markdown format.
TypeScript
23.6K
5 points

Unity
Certified
UnityMCP is a Unity editor plugin that implements the Model Context Protocol (MCP), providing seamless integration between Unity and AI assistants, including real - time state monitoring, remote command execution, and log functions.
C#
19.2K
5 points

Figma Context MCP
Framelink Figma MCP Server is a server that provides access to Figma design data for AI programming tools (such as Cursor). By simplifying the Figma API response, it helps AI more accurately achieve one - click conversion from design to code.
TypeScript
44.5K
4.5 points

Minimax MCP Server
The MiniMax Model Context Protocol (MCP) is an official server that supports interaction with powerful text-to-speech, video/image generation APIs, and is suitable for various client tools such as Claude Desktop and Cursor.
Python
30.3K
4.8 points

Context7
Context7 MCP is a service that provides real-time, version-specific documentation and code examples for AI programming assistants. It is directly integrated into prompts through the Model Context Protocol to solve the problem of LLMs using outdated information.
TypeScript
62.9K
4.7 points





