OakVar MCP Server

OakVar MCP Server

Enables AI assistants to perform genomic variant analysis using OakVar, including running annotation pipelines, managing 200+ annotator modules, querying variant databases, and generating reports in various formats.

Category
Visit Server

README

OakVar MCP Server

A Model Context Protocol (MCP) server that exposes OakVar's genomic variant analysis capabilities to AI assistants.

Supported MCP Clients: Claude Desktop, ChatGPT Desktop, and other MCP-compatible clients.

Quick Start

# 1. Install OakVar and the MCP server
pip install oakvar oakvar-mcp

# 2. Setup OakVar (first time only)
ov system setup

# 3. Configure your MCP client (see SETUP.md)

šŸ“– Full setup instructions: See SETUP.md

What is This?

This MCP server lets you control OakVar through AI assistants like Claude or ChatGPT. Instead of running command-line tools, you can simply ask:

  • "What OakVar modules are installed?"
  • "Install the ClinVar annotator"
  • "Run OakVar on my VCF file with gnomAD annotation"
  • "Show me pathogenic variants from the results"

Features

Category Capabilities
Pipeline Run annotations, generate reports (VCF, Excel, CSV)
Modules Install, update, list, search 200+ annotator modules
Data Query result databases, filter variants, export data
Development Create module templates, pack for distribution

Architecture

ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”     MCP Protocol     ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”
│   Claude /      │◄────────────────────►│  OakVar MCP      │
│   ChatGPT       │    (stdin/stdout)    │     Server       │
ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜                      ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”¬ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜
                                                  │
                                                  │ Python API
                                                  ā–¼
                                         ā”Œā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”
                                         │     OakVar       │
                                         │ Variant Analysis │
                                         ā””ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”€ā”˜

Installation

Note: OakVar and this MCP server must be installed in the same Python environment. If you use a virtual environment, configure your MCP client to use the full path to that environment's oakvar-mcp executable.

<!--

From PyPI

pip install oakvar-mcp

-->

From Source

git clone https://github.com/zaroganos/oakvar-mcp.git
cd oakvar-mcp
pip install -e .

Configuration

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "oakvar": {
      "command": "oakvar-mcp"
    }
  }
}

ChatGPT Desktop

Add to chatgpt_mcp_config.json:

{
  "mcpServers": {
    "oakvar": {
      "command": "oakvar-mcp"
    }
  }
}

šŸ“– Config file locations and troubleshooting: See SETUP.md

Available Tools (19)

Tool Description
oakvar_version Get OakVar version
oakvar_system_check Verify installation
oakvar_system_setup Configure OakVar
oakvar_modules_dir Get/set modules directory
oakvar_module_list List modules
oakvar_module_info Get module details
oakvar_module_install Install modules
oakvar_module_uninstall Remove modules
oakvar_module_update Update modules
oakvar_run Run annotation pipeline
oakvar_report Generate reports
oakvar_sqliteinfo Get database info
oakvar_filtersqlite Filter databases
oakvar_query Execute SQL queries
oakvar_new_module Create module templates
oakvar_new_exampleinput Create test inputs
oakvar_module_pack Pack for distribution
oakvar_store_fetch Refresh store cache
oakvar_store_register Register modules

Development

# Clone and install in dev mode
git clone https://github.com/zaroganos/oakvar-mcp.git
cd oakvar-mcp
pip install -e ".[dev]"

# Run tests
pytest tests/ -v

Project Structure

oakvar-mcp/
ā”œā”€ā”€ oakvar_mcp/
│   ā”œā”€ā”€ __init__.py
│   ā”œā”€ā”€ __main__.py
│   └── server.py
ā”œā”€ā”€ tests/
│   └── test_server.py
ā”œā”€ā”€ pyproject.toml
ā”œā”€ā”€ README.md
ā”œā”€ā”€ SETUP.md
ā”œā”€ā”€ claude_desktop_config.example.json
└── chatgpt_mcp_config.example.json

License

MIT License

Links

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured