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Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

Search foods, compare nutrients, and look up the full USDA FoodData Central database.

README.md

<div align="center"> <h1>@cyanheads/usda-mcp-server</h1> <p><b>Search foods, compare nutrients, and look up the full USDA FoodData Central database via MCP. STDIO or Streamable HTTP.</b> <div>5 Tools • 2 Resources</div> </p> </div>

<div align="center">

![Version](./CHANGELOG.md) ![License](./LICENSE) ![Docker](https://github.com/users/cyanheads/packages/container/package/usda-mcp-server) ![MCP SDK](https://modelcontextprotocol.io/) ![npm](https://www.npmjs.com/package/@cyanheads/usda-mcp-server) ![TypeScript](https://www.typescriptlang.org/) ![Bun](https://bun.sh/)

</div>

<div align="center">

![Install in Claude Desktop](https://github.com/cyanheads/usda-mcp-server/releases/latest/download/usda-mcp-server.mcpb) ![Install in Cursor](https://cursor.com/en/install-mcp?name=usda-mcp-server&config=eyJjb21tYW5kIjoibnB4IiwiYXJncyI6WyIteSIsIkBjeWFuaGVhZHMvdXNkYS1tY3Atc2VydmVyIl0sImVudiI6eyJVU0RBX0ZEQ19BUElfS0VZIjoieW91ci1hcGkta2V5In19) ![Install in VS Code](https://vscode.dev/redirect?url=vscode:mcp/install?%7B%22name%22%3A%22usda-mcp-server%22%2C%22command%22%3A%22npx%22%2C%22args%22%3A%5B%22-y%22%2C%22%40cyanheads%2Fusda-mcp-server%22%5D%2C%22env%22%3A%7B%22USDA_FDC_API_KEY%22%3A%22your-api-key%22%7D%7D)

![Framework](https://www.npmjs.com/package/@cyanheads/mcp-ts-core)

</div>

---

Tools

Five tools covering the USDA FoodData Central workflow — from discovery to detailed nutrient analysis:

| Tool | Description | |:---|:---| | usda_search_foods | Search foods by keyword across SR Legacy, Foundation, Survey FNDDS, and Branded data sources, with nutrient preview and pagination | | usda_get_food | Full nutrient profile for one food by FDC ID, with optional per-portion scaling (g, oz, lb, kg, or serving) | | usda_get_foods | Batch nutrient fetch for 2–20 FDC IDs in a single request; failed IDs reported in failed[] instead of aborting | | usda_compare_foods | Side-by-side nutrient comparison for 2–5 foods, formatted as a markdown table scaled to a common gram basis | | usda_list_nutrients | Static FDC nutrient reference table (~150 nutrients) with IDs, names, units, and categories — no API call required |

usda_search_foods

Search USDA FoodData Central foods by keyword, UPC/GTIN code, or ingredient.

  • Covers all FDC data sources: SR Legacy (common whole foods, complete nutrient profiles), Foundation, Survey FNDDS, and Branded (packaged products)
  • Defaults to SR Legacy; include "Branded" in dataType for packaged products or UPC lookup
  • Brand owner filter to narrow branded results (e.g. "General Mills")
  • Food category filter (e.g. "Poultry Products", "Vegetables and Vegetable Products")
  • Pagination via pageSize (up to 50) and pageNumber
  • Returns FDC IDs and a preview of key nutrients (energy, protein, fat, carbs) — use usda_get_food for the full profile

---

usda_get_food

Full nutrient profile for one food by FDC ID.

  • All available nutrients (or a filtered subset via nutrients[]) with amounts per 100g
  • Optional portion scaling — provide quantity + unit to scale values (e.g. quantity=200, unit="g" → per-200g values)
  • unit="serving" scales to the food's first defined portion weight
  • Returns all named portion definitions (allPortions[]) alongside the serving info
  • Filtering nutrients[] to specific IDs strongly reduces context size for common queries (use usda_list_nutrients to look up IDs)

---

usda_get_foods

Batch nutrient fetch for 2–20 FDC IDs.

  • All values per 100g (no portion scaling in batch mode)
  • nutrients[] filter strongly recommended — full profiles for 20 foods are large
  • Per-item partial failure: failed[] carries IDs that returned no data, so one missing food doesn't abort the batch
  • More efficient than N individual usda_get_food calls when you already have FDC IDs

---

usda_compare_foods

Side-by-side nutrient comparison for 2–5 foods.

  • Returns a pivot table — one row per nutrient, one column per food — and formats it as a markdown table
  • Defaults to the 12 most commonly compared nutrients (energy, protein, fat, saturated fat, carbs, fiber, sugars, sodium, potassium, calcium, iron, vitamin C)
  • Pass custom nutrients[] for specific comparisons (e.g. just iron and vitamin C)
  • All values scaled to a common gram basis (default 100g; override with quantity + unit)
  • Proceeds with valid foods when some IDs aren't found — only fails when fewer than 2 IDs return data
  • Rows where all values are null (nutrient not tracked for any of the selected foods) are filtered out

---

usda_list_nutrients

FDC nutrient reference table — all ~150 tracked nutrients.

  • Returns IDs, names, SR reference numbers, units, and categories
  • Optional category filter: macronutrients, vitamins, minerals, lipids, amino_acids, other
  • Resolves nutrient names (e.g. "vitamin C") to FDC IDs (1162) for use in nutrients[] params
  • Static data — no API call, instant response; call once and reuse the IDs

Resources and prompts

| Type | Name | Description | |:---|:---|:---| | Resource | usda://food/{fdcId} | Full nutrient profile for a specific food by FDC ID — same data as usda_get_food without portion scaling | | Resource | usda://nutrients | Complete FDC nutrient reference list — all ~150 tracked nutrients with IDs, names, units, and categories |

All resource data is also reachable via tools. Use usda_search_foods to discover FDC IDs before reading food resources.

Features

Built on @cyanheads/mcp-ts-core:

  • Declarative tool and resource definitions — single file per primitive, framework handles registration and validation
  • Unified error handling — handlers throw, framework catches, classifies, and formats
  • Pluggable auth: none, jwt, oauth
  • Swappable storage backends: in-memory, filesystem, Supabase, Cloudflare KV/R2/D1
  • Structured logging with optional OpenTelemetry tracing
  • STDIO and Streamable HTTP transports

USDA FDC-specific:

  • Type-safe client for the USDA FoodData Central REST API (api.nal.usda.gov/fdc/v1)
  • Normalization layer that handles inconsistent API response shapes across search, single-food, and batch endpoints
  • Batch API endpoint (/foods) with per-food partial failure reporting
  • HTML response detection (rate-limit proxy returns 200 HTML) with service-unavailable error surfacing
  • Static nutrient reference dictionary — ~150 nutrients with FDC IDs, SR numbers, units, and categories; no API call required

Agent-friendly output:

  • Provenance preserved — FDC data source (dataType) on every food result so callers know whether they're reading curated research data or label-derived branded values
  • Partial failure reporting — batch tools (usda_get_foods, usda_compare_foods) return successes alongside structured failed[] / missingData[] entries rather than failing the whole request
  • Cross-reference hints — FDC IDs and tool names in descriptions so agents know exactly which call to make next (search → get → compare workflow)

Getting started

Add the following to your MCP client configuration file. See data.gov API key signup to generate a free API key.

{
  "mcpServers": {
    "usda-mcp-server": {
      "type": "stdio",
      "command": "bunx",
      "args": ["@cyanheads/usda-mcp-server@latest"],
      "env": {
        "MCP_TRANSPORT_TYPE": "stdio",
        "MCP_LOG_LEVEL": "info",
        "USDA_FDC_API_KEY": "your-api-key"
      }
    }
  }
}

Or with npx (no Bun required):

{
  "mcpServers": {
    "usda-mcp-server": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@cyanheads/usda-mcp-server@latest"],
      "env": {
        "MCP_TRANSPORT_TYPE": "stdio",
        "MCP_LOG_LEVEL": "info",
        "USDA_FDC_API_KEY": "your-api-key"
      }
    }
  }
}

Or with Docker:

{
  "mcpServers": {
    "usda-mcp-server": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-e", "MCP_TRANSPORT_TYPE=stdio",
        "-e", "USDA_FDC_API_KEY=your-api-key",
        "ghcr.io/cyanheads/usda-mcp-server:latest"
      ]
    }
  }
}

For Streamable HTTP, set the transport and start the server:

MCP_TRANSPORT_TYPE=http MCP_HTTP_PORT=3010 USDA_FDC_API_KEY=your-api-key bun run start:http
# Server listens at http://localhost:3010/mcp

Prerequisites

  • Bun v1.3.2 or higher (or Node.js v24+).
  • A free USDA FDC API key — register at api.data.gov/signup. The key is required; without it the server will not start.

Installation

  1. Clone the repository:
git clone https://github.com/cyanheads/usda-mcp-server.git
  1. Navigate into the directory:
cd usda-mcp-server
  1. Install dependencies:
bun install
  1. Configure environment:
cp .env.example .env
# edit .env and set USDA_FDC_API_KEY

Configuration

| Variable | Description | Default | |:---------|:------------|:--------| | USDA_FDC_API_KEY | Required. USDA FoodData Central API key from api.data.gov. | — | | MCP_TRANSPORT_TYPE | Transport: stdio or http. | stdio | | MCP_HTTP_PORT | Port for HTTP server. | 3010 | | MCP_AUTH_MODE | Auth mode: none, jwt, or oauth. | none | | MCP_LOG_LEVEL | Log level (RFC 5424). | info | | LOGS_DIR | Directory for log files (Node.js only). | <project-root>/logs | | STORAGE_PROVIDER_TYPE | Storage backend. | in-memory | | OTEL_ENABLED | Enable OpenTelemetry instrumentation (spans, metrics, completion logs). | false |

See .env.example for the full list of optional overrides.

Running the server

Local development

  • Build and run:
  # One-time build
  bun run rebuild

  # Run the built server
  bun run start:stdio
  # or
  bun run start:http
  • Run checks and tests:
  bun run devcheck   # Lint, format, typecheck, security
  bun run test       # Vitest test suite
  bun run lint:mcp   # Validate MCP definitions against spec

Docker

docker build -t usda-mcp-server .
docker run --rm -e USDA_FDC_API_KEY=your-key -p 3010:3010 usda-mcp-server

The Dockerfile defaults to HTTP transport, stateless session mode, and logs to /var/log/usda-mcp-server. OpenTelemetry peer dependencies are installed by default — build with --build-arg OTEL_ENABLED=false to omit them.

Project structure

| Directory | Purpose | |:----------|:--------| | src/index.ts | createApp() entry point — registers tools, resources, and inits FdcService. | | src/config | Server-specific environment variable parsing and validation with Zod (USDA_FDC_API_KEY). | | src/mcp-server/tools | Tool definitions (.tool.ts) — search, get, batch, compare, list-nutrients. | | src/mcp-server/resources | Resource definitions (.resource.ts) — food profile and nutrient reference. | | src/services/fdc | FdcService — USDA FDC API client, normalization, and static nutrient reference data. | | tests/ | Unit tests mirroring src/ — 50 tests across all tools and resources. |

Development guide

See CLAUDE.md for development guidelines and architectural rules. The short version:

  • Handlers throw, framework catches — no try/catch in tool logic
  • Use ctx.log for request-scoped logging, ctx.state for tenant-scoped storage
  • Register new tools and resources via the barrels in src/mcp-server/*/definitions/index.ts
  • Wrap external API calls: validate raw → normalize to domain type → return output schema; never fabricate missing fields

Contributing

Issues and pull requests are welcome. Run checks and tests before submitting:

bun run devcheck
bun run test

License

Apache-2.0 — see LICENSE for details.

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