dbSNP MCP Plugin: Automate SNP Pipelines & Streamline Variant Analysis

DbSNP MCP Plugin: Finally, a rock-solid tool to tame SNP chaos. Streamlines variant handling, automates data pipelines, and slashes analysis time. Science made painlessly efficient. 🧬🚀

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About dbSNP MCP Plugin

What is dbSNP MCP Plugin: Automate SNP Pipelines & Streamline Variant Analysis?

dbSNP MCP Plugin is a purpose-built tool designed to integrate NCBI's dbSNP database directly into computational workflows, enabling seamless access to genetic variant data through Python-based environments. By abstracting complex API interactions, this plugin empowers researchers to automate SNP analysis pipelines while maintaining rigorous data integrity standards.

Key Features of dbSNP MCP Plugin

RS ID Resolution: Instantly fetch comprehensive SNP details using standardized rs identifiers
Contextual Search: Leverage flexible search parameters including gene symbols, phenotypic associations, and genomic coordinates
Clinical Context: Retrieve FDA-recognized clinical significance classifications and variant impact annotations
Rate Limit Management: Built-in support for NCBI API keys to maximize query throughput

dbSNP MCP Plugin Features

How to Use dbSNP MCP Plugin

Setup Process

Begin by ensuring Python 3.7+ and the MCP CLI are installed. Configure the plugin via:

pip install mcp requests && mcp install server.py

For production environments, register an NCBI API key to unlock higher query rates (up to 10/s).

Core Functionality

Single-SNP Analysis: mcp.dbsnp.get_snp_by_rs("rs6311")
Batch Queries: mcp.dbsnp.search_snps("BRCA1", limit=5)
Clinical Reporting: mcp.dbsnp.get_snp_clinical_significance() for regulatory submissions

Use Cases of dbSNP MCP Plugin

Researchers leverage this tool in:

Pharmacogenomics studies requiring CLINVAR annotations
Variant prioritization in whole-genome sequencing pipelines
Automated SNP tracking across longitudinal cohort studies
Compliance-driven reporting for clinical diagnostics

dbSNP MCP Plugin FAQ

FAQ: Common Implementation Considerations

How do I resolve authentication errors?

Verify your API key at NCBI's authentication portal. Ensure key permissions include dbSNP access.

What response formats are supported?

Returns standardized JSON objects with assembly, chromosome, and clinical_significance fields for programmatic processing.

Content

dbSNP MCP Plugin

This MCP plugin allows you to retrieve genetic variant information from NCBI's dbSNP database directly in your development environment.

Features

Retrieve detailed information about SNPs using rs IDs
Search for SNPs by various terms (gene names, phenotypes, etc.)
Get clinical significance information for variants

Installation

Prerequisites

Python 3.7+
MCP CLI tool

Setup

Install the required dependencies:

pip install mcp requests

Install the MCP server:

mcp install server.py

(Optional) To use higher rate limits, get an NCBI API key and add it to your configuration:

mcp install server.py -v NCBI_API_KEY=your_api_key_here

Usage

Get SNP by rs ID

Retrieves detailed information about a specific SNP by its rs ID.

# Example: Get details for rs6311
result = mcp.dbsnp.get_snp_by_rs("rs6311")

Search for SNPs

Search for SNPs using various terms like gene names or phenotypes.

# Example: Search for SNPs related to BRCA1
results = mcp.dbsnp.search_snps("BRCA1", limit=5)

Get Clinical Significance

Retrieve clinical significance data for a specific SNP.

# Example: Get clinical significance for rs397507444
clinical_data = mcp.dbsnp.get_snp_clinical_significance("rs397507444")

Rate Limits

Without an API key, NCBI limits requests to 3 per second. With an API key, you can make up to 10 requests per second.

To obtain an NCBI API key:

Register for an NCBI account at https://www.ncbi.nlm.nih.gov/
Go to your account settings to generate an API key

Troubleshooting

If you encounter issues:

Check your internet connection
Verify the rs ID format is correct
Ensure your API key is valid (if using one)
Check the error messages for specific API response issues

License

MIT