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nexonco-mcp

MCP.Pizza Chef: Nexgene-Research

Nexonco-mcp is an advanced MCP server designed to access and analyze clinical evidence data from the CIViC database. It offers fast, flexible search capabilities across genetic variants, diseases, drugs, and phenotypes, enabling precision medicine and oncology research workflows. This server supports researchers and clinicians by providing structured, real-time access to critical clinical variant interpretations to inform cancer treatment decisions.

Use This MCP server To

Search clinical evidence for cancer-related genetic variants Query drug-variant interactions for oncology research Retrieve phenotype associations with cancer variants Support precision medicine decisions with clinical data Integrate CIViC clinical evidence into AI workflows Enable flexible multi-parameter searches on clinical data Provide structured clinical variant data for LLM agents

README

nexonco-mcp-banner

Nexonco by Nexgene Research is an MCP server for accessing clinical evidence from the CIViC (Clinical Interpretation of Variants in Cancer) database. It enables fast, flexible search across variants, diseases, drugs, and phenotypes to support precision oncology.

PyPI NANDA License

Demo

nexonco-mcp-demo.mp4

Watch full video here: Youtube

Setup

Prerequisites

  • uv or Docker
  • Claude Desktop (for MCP integration)

Setup Guides

For detailed setup instructions, refer to the following documentation:

  • NANDA Host Setup
    See docs/nanda-server-setup.md for backend configuration and local registration of the NANDA Server.

  • Claude Desktop Setup
    See docs/claude-desktop-setup.md for guidance on configuring the local development environment and MCP integration.

These guides include all required steps, environment configurations, and usage notes to get up and running.

Tool List

search_clinical_evidence: A MCP tool for querying clinical evidence data that returns formatted reports.

Input Schema

The tool accepts the following optional parameters:

  • disease_name (str): Filter by disease (e.g., "Lung Non-small Cell Carcinoma").
  • therapy_name (str): Filter by therapy or drug (e.g., "Cetuximab").
  • molecular_profile_name (str): Filter by gene or variant (e.g., "EGFR L858R").
  • phenotype_name (str): Filter by phenotype (e.g., "Chest Pain").
  • evidence_type (str): Filter by evidence type (e.g., "PREDICTIVE", "DIAGNOSTIC").
  • evidence_direction (str): Filter by evidence direction (e.g., "SUPPORTS").
  • filter_strong_evidence (bool): If True, only includes evidence with a rating > 3 (max 5).

Output

The tool returns a formatted string with four sections:

  1. Summary Statistics:
    • Total evidence items
    • Average evidence rating
    • Top 3 diseases, genes, variants, therapies, and phenotypes (with counts)
  2. Top 10 Evidence Entries:
    • Lists the highest-rated evidence items with details like disease, phenotype, gene/variant, therapy, description, type, direction, and rating.
  3. Sources & Citations:
    • Citations and URLs for the sources of the top 10 evidence entries.
  4. Disclaimer:
    • A note stating the tool is for research purposes only, not medical advice.

Sample Usage

  • "Find predictive evidence for colorectal cancer therapies involving KRAS mutations."
  • "Are there studies on Imatinib for leukemia?"
  • "What therapies are linked to pancreatic cancer evidence?"

Acknowledgements

  • Model Context Protocol
  • NANDA: The Internet of AI Agents
  • CIViC - Clinical Interpretation of Variants in Cancer

License

This project is licensed under the MIT License - see the LICENSE file for details.

Disclaimer

⚠️ This tool is intended exclusively for research purposes. It is not a substitute for professional medical advice, diagnosis, or treatment.

Contributors

  • Obada Qasem (@obadaqasem), Nexgene AI
  • Kutsal Ozkurt (@Goodsea), Nexgene AI

nexonco-mcp FAQ

How do I install nexonco-mcp?
You can install nexonco-mcp via PyPI using 'pip install nexonco-mcp'.
What clinical data sources does nexonco-mcp use?
It primarily accesses the CIViC database for clinical variant evidence in cancer.
Can nexonco-mcp handle complex queries across multiple clinical parameters?
Yes, it supports flexible, multi-parameter searches across variants, diseases, drugs, and phenotypes.
Is nexonco-mcp compatible with different LLM providers?
Yes, it is provider-agnostic and works with OpenAI, Anthropic Claude, and Google Gemini models.
How does nexonco-mcp ensure data relevance for precision oncology?
By leveraging curated clinical evidence from CIViC, it provides up-to-date variant interpretations relevant to cancer treatment.
Can I integrate nexonco-mcp into existing AI workflows?
Yes, it is designed to be integrated into AI-enhanced workflows and MCP clients for real-time clinical data access.
What programming languages are supported for interacting with nexonco-mcp?
It provides a Python package for easy integration, but can be accessed via standard MCP protocols from any language.
Does nexonco-mcp support phenotype-based searches?
Yes, it allows searching clinical evidence by phenotypes associated with cancer variants.