MCP Server

GeneOps speaks MCP (Model Context Protocol) — the open standard for connecting AI agents to external data. Hook up any compatible agent and it gets structured access to your genomics results, action items, and the full research database.

Don’t have an MCP agent yet?

Any agent that speaks MCP will work. Two good options:

Claude Code by Anthropic

Terminal agent with native MCP support. Great for in-depth research sessions.

npm install -g @anthropic-ai/claude-code
OpenCode open source

Open-source terminal agent. Bring any model — including local ones via Ollama.

curl -fsSL https://opencode.ai/install | bash

Also works with ChatGPT desktop, Cursor, Windsurf, Cline, and any other MCP client.

Get your API key

Your API key authenticates your agent with GeneOps.

Go to Account to generate your API key.

Add the server config

Add this to your agent’s MCP server configuration, replacing the key with your own: 

{
  "type": "url",
  "url": "https://geneops.ai/mcp",
  "headers": {
    "Authorization": "Bearer YOUR_API_KEY"
  }
}

Claude Code: Add to ~/.claude/settings.json under "mcpServers": 

{
  "mcpServers": {
    "geneops": {
      "type": "url",
      "url": "https://geneops.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

OpenCode: Add to ~/.opencode/config.jsonc under "mcpServers" using the same format.

Other agents: Check your agent’s MCP docs — the server config object is the same everywhere.

Available tools

Your agent gets four tools — the same data our built-in agent uses.

get_my_dashboard

Full overview: matched variants, health profile, per-category findings with severity flags and recommendations.

get_my_actionables

All your resolved action items. Filter by type (supplement, diet, lifestyle, monitoring, avoidance) or health category.

get_my_genotype

Deep dive on any single variant by rsID. Returns your alleles, interpretation, severity, and personalized action items.

knowledge_base

Browse or search the full research database: categories, SNPs, articles, population frequencies, genotype interpretations.

What this gives you

Cross-reference with your own documents. Point your agent at lab results, doctor’s notes, or research papers on your machine.

Choose your own model. Run Llama or Mistral locally, or use Claude, GPT, Gemini. MCP is model-agnostic.

Long-running health research. Query your genotype data, search PubMed, read new studies, keep notes across sessions.

Try asking

“Give me an overview of my results and the most important findings.”

“My homocysteine came back at 14 μmol/L. Is that related to any of my variants?”

“Cross-reference my pharmacogenomics profile with my current medications.”

“Build me a supplement stack based on my actual genetic needs.”

A note on privacy

The MCP server returns your structured genetic data to whatever agent you connect. If you pair it with a local model via Ollama, your data never leaves your machine — only the tool calls hit our server. We don’t log tool call contents.

If you use a cloud model, your data is governed by that provider’s privacy policy. Either way — you choose.

Don’t need your own agent?

GeneOps has a built-in AI agent powered by Claude Sonnet. It has access to the same tools and data — no setup, no API key, works in your browser.

The trade-off: with MCP you choose the model, can use local models for full privacy, and can cross-reference your own files (lab results, medical records, research papers). The built-in agent is simpler but runs on our infrastructure and your queries go through Anthropic’s API.

Try the built-in agent