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MCP Server · Model Context Protocol · 2026

Use Lifespan Vault from inside your AI.

Lifespan Vault publishes an MCP (Model Context Protocol) server at /api/mcp , add it to Claude Desktop, Cursor, or any MCP-aware client and our 99-product editorial catalog, comparison data, and capital allocator become callable tools inside your AI workflow.

When this is useful

  • You're researching longevity hardware purchases and want editorial scoring + comparison data inside your existing AI chat instead of switching tabs.
  • You're building an AI agent or workflow that recommends products to clients (concierge medical practice, family office, fitness coach) and need a vetted source of truth.
  • You're a developer exploring the MCP ecosystem and want a clean, CC-BY 4.0-licensed reference server with 5 production tools.

Install, Claude Desktop

Edit your claude_desktop_config.json, on macOS at ~/Library/Application Support/Claude/claude_desktop_config.json and on Windows at %APPDATA%\Claude\claude_desktop_config.json. Restart Claude Desktop after saving.

{
  "mcpServers": {
    "lifespan-vault": {
      "url": "https://lifespanvault.com/api/mcp"
    }
  }
}

Install, Cursor

In Cursor, open Settings → MCP Servers → New MCP Server, paste the config below, and reload the workspace.

{
  "mcpServers": {
    "lifespan-vault": {
      "url": "https://lifespanvault.com/api/mcp",
      "type": "http"
    }
  }
}

Install, Continue

Add to your ~/.continue/config.yaml:

experimental:
  modelContextProtocolServers:
    - transport:
        type: http
        url: https://lifespanvault.com/api/mcp

What you can call

5 tools, JSON-RPC 2.0 over HTTP. Each is callable directly by your AI client once the server is installed.

search_catalog

Search the full catalog by query, persona, budget cap, or category. Returns ranked products with scoring rationale.

Try: "Find me red light therapy panels under $500 with high editorial scores."
compare_products

Side-by-side comparison between any two products in the catalog. Returns spec deltas, price gaps, and editorial verdicts.

Try: "Compare the Sunlighten mPulse Empower with the Clearlight Sanctuary 5."
get_product

Pull the full review for a single product, spotlight body, deep review, score, specs, FAQs, and competitors considered.

Try: "What's the full review of the Oura Ring Gen 4?"
allocate_capital

Given a budget and persona (founder, family-office, longevity-pro, athlete, healthspan-60+), returns an optimized longevity hardware stack.

Try: "Allocate $25,000 for a 50-year-old founder building a home longevity stack."
get_compatibility

Cross-ecosystem integration data, which wearables export to which apps, which CGMs sync with which platforms, which products pair natively.

Try: "Does the Omni Health Ring export to Apple Health?"

Not using an MCP-aware client?

Lifespan Vault is also available as the Lifespan Vault Concierge custom GPT on the OpenAI GPT Store. Same 99-product catalog, same editorial scoring rubric, accessible to anyone with a ChatGPT account. The GPT calls the same backend APIs the MCP server exposes, both channels stay in sync.

Launching on the GPT Store soon. Email ryan@lifespanvault.com for early access.

Developer documentation