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Pay-per-call USDA nutrition for AI agents (x402 micropayments in USDC on Base).
Pay-per-call USDA nutrition for AI agents (x402 micropayments in USDC on Base).
Valid MCP server (2 strong, 4 medium validity signals). No known CVEs in dependencies. Imported from the Official MCP Registry.
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From the project's GitHub README.
Pay-per-call USDA nutrition data for AI agents. Structured FoodData Central via the x402 micropayment protocol — agents pay $0.001–$0.005 in USDC per request, no signup, no API keys, no human auth flows.
Live at https://nutriref.xyz. Spec at /openapi.json · Swagger at /docs · Bazaar discovery at /.well-known/x402.
| Method | Path | Price | Cache |
|---|---|---|---|
GET | /v1/nutrition/search?q=&limit= | $0.001 | 24h |
GET | /v1/nutrition/detail/{fdc_id} | $0.002 | 7d |
POST | /v1/nutrition/compare | $0.003 | derived |
POST | /v1/nutrition/recipe | $0.005 | derived |
All values per 100g. Missing nutrients are null, not 0. compare returns per-nutrient winners (highest protein, lowest sodium, etc.). recipe scales by grams and sums.
NutriRef ships an MCP server that exposes the four endpoints as native tools. Install once:
git clone https://github.com/Younghef/nutriref-api.git
cd nutriref-api
pip install -e ".[mcp]"
A PyPI release is planned. Until then the source install above is the supported path.
Then add this to your MCP client config (Claude Desktop's claude_desktop_config.json, Claude Code's MCP settings, etc.):
{
"mcpServers": {
"nutriref": {
"command": "python",
"args": ["-m", "mcp_server"],
"env": {
"PAYER_PRIVATE_KEY": "0x...your-funded-wallet-key...",
"NUTRIREF_BASE_URL": "https://nutriref.xyz"
}
}
}
}
The wallet needs USDC on Base mainnet — gas is sponsored by the facilitator, so you only need stablecoin balance. The agent now has nutrition_search, nutrition_detail, nutrition_compare, nutrition_recipe and auto-pays per call.
Unpaid requests get 402 Payment Required with x402 payment instructions. Any x402-aware client signs a gasless USDC authorization (EIP-3009) and retries automatically:
import asyncio
from eth_account import Account
from x402.client import x402Client
from x402.http.clients.httpx import wrapHttpxWithPayment
from x402.mechanisms.evm.exact import register_exact_evm_client
account = Account.from_key("0x...funded-wallet-key...")
client = x402Client(); register_exact_evm_client(client, account)
async def main():
async with wrapHttpxWithPayment(client, base_url="https://nutriref.xyz") as http:
r = await http.get("/v1/nutrition/detail/2012128")
print(r.json())
asyncio.run(main())
GET /v1/nutrition/detail/173944:
{
"fdc_id": 173944,
"description": "Banana, raw",
"data_type": "Foundation",
"serving_size": 100, "serving_size_unit": "g",
"calories": 89.0, "protein": 1.1, "fat": 0.3,
"carbs": 22.8, "fiber": 2.6, "sugar": 12.2,
"sodium": 1.0, "cholesterol": null, "saturated_fat": 0.1,
"vitamin_c": 8.7, "calcium": 5.0, "iron": 0.3, "potassium": 358.0
}
NutriRef is open source; the live instance at nutriref.xyz is one deployment among many possible. To run your own:
cp .env.example .env
# fill in USDA_API_KEY (free at https://fdc.nal.usda.gov/api-key-signup.html)
# and X402_RECEIVER_ADDRESS (an EVM address that should receive payments)
docker compose up --build
curl http://localhost:8000/health
| Var | Required | Default | Purpose |
|---|---|---|---|
USDA_API_KEY | yes | — | Free key from fdc.nal.usda.gov |
USDA_BASE_URL | no | https://api.nal.usda.gov/fdc/v1 | |
REDIS_URL | no | redis://redis:6379/0 | Response cache |
X402_NETWORK | no | base-sepolia | base for mainnet |
X402_RECEIVER_ADDRESS | yes | — | EVM address that receives USDC |
X402_FACILITATOR_URL | no | https://x402.org/facilitator | https://api.cdp.coinbase.com for mainnet |
CDP_API_KEY_ID | mainnet only | — | Coinbase Developer Platform key ID |
CDP_API_KEY_SECRET | mainnet only | — | Coinbase Developer Platform key secret |
LOG_LEVEL | no | INFO |
For mainnet you need a Coinbase CDP account and the public x402 facilitator at https://api.cdp.coinbase.com. Testnet works for free with the community facilitator at https://x402.org/facilitator.
agent → x402 middleware → route handler → cache (Redis) → USDA FDC API
search and detail cache USDA responses directly. compare and recipe compose from the cached detail data — no extra USDA calls when warm. The cache is a meaningful cost lever: warm requests return in <50ms and never hit USDA.
pip install -e ".[dev]"
pytest
examples/meal-planner/ is a complete, ~150-line agent that gives Claude
the four NutriRef endpoints as tools and asks it to plan a day of meals
hitting a calorie/protein goal. Worth reading if you're wiring NutriRef
into your own agent — the tool schemas and the payment loop are all
there. See examples/meal-planner/README.md.
app/ # FastAPI service
main.py # app factory + x402 init
routes/ # search, detail, compare, recipe
landing.py # / (public landing page)
discovery.py # /.well-known/x402, /llms.txt, /.well-known/ai-plugin.json, /logo.svg
usda.py # async USDA client
cache.py # Redis wrapper
normalize.py # USDA → flat 13-nutrient schema
mcp_server/ # MCP server wrapper for agent use
examples/ # worked agent examples (meal planner)
scripts/ # CDP wallet bootstrap + payer-side test
tests/ # pytest + respx + fakeredis
fastapi-x402 for the server middleware (with a small EIP-712 patch we apply at startup for Base mainnet USDC).Be the first to review this server!
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