Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@mcp-usda-fdc search for low-carb vegetables"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
USDA Food Data Central MCP — comprehensive nutrient database for US foods (~600k items across SR Legacy, Foundation, Survey, Branded, Experimental data types).
Part of Pipeworx — an MCP gateway connecting AI agents to 1476+ live data sources.
search_foods(query, data_type?, page_size?, page_number?, sort_by?, sort_order?, brand_owner?)
get_food(fdc_id, format?, nutrients?) — single-food detail
list_foods(data_type?, page_size?, page_number?, sort_by?, sort_order?) — browse
list_food_groups() — USDA food group reference
nutrients_for_food(fdc_id, nutrient_numbers?) — convenience: just the nutrient values
Related MCP server: Food Data Central MCP Server
Platform key: gateway env PLATFORM_USDA_FDC_KEY
BYO: ?_apiKey=<key> after registering at https://api.data.gov/signup/
Free tier: 1000 req/hour.
https://api.nal.usda.gov/fdc/v1/ — api_key= query param.
Add to your MCP client (Claude Desktop, Cursor, Windsurf, etc.):
{
"mcpServers": {
"usda-fdc": {
"url": "https://gateway.pipeworx.io/usda-fdc/mcp"
}
}
}tools/list at https://gateway.pipeworx.io/usda-fdc/mcp returns the tools in the table
above plus the shared Pipeworx meta-tools — ask_pipeworx,
discover_tools, search_within, remember/recall and the rest of the
gateway-wide set. So the tool count you see is larger than this table: a
single-pack endpoint currently lists roughly 30 shared tools alongside the
pack's own. The connection's initialize response states its exact scope, and
is the authoritative answer for a given day.
This is deliberate, not multiplexing by accident. The meta-tools are what let a
scoped connection answer a question this pack does not cover — via
ask_pipeworx, which routes across the whole catalog — without you adding a
second MCP server. There is currently no way to mount a pack endpoint without
them; if the extra schemas cost you more context than the routing is worth,
connect to the full gateway once rather than to several pack endpoints.
Or connect to the full Pipeworx gateway to get every pack's tools listed directly, instead of just this one's:
{
"mcpServers": {
"pipeworx": {
"url": "https://gateway.pipeworx.io/mcp"
}
}
}Both URLs reach the same gateway and the same 1476+ data sources. The
only difference is which pack's tools are listed directly; ask_pipeworx
reaches all of them from either one.
Instead of calling tools directly, you can ask questions in plain English — this works on the pack endpoint above as well as on the full gateway:
ask_pipeworx({ question: "your question about Usda Fdc data" })The gateway picks the right tool and fills the arguments automatically.
MIT
This server cannot be deployed
Scraps Kitchen gives any AI agent a persistent, household-aware kitchen memory. Unlike generic chatbot recall, Scraps maintains structured cooking data: what's in your fridge (with freshness tracking), who you cook for (with allergens, dietary restrictions, and preferences), your recipe collection (with cook notes and per-diner ratings), your shopping list, and your kitchen equipment. 27 tools across 6 domains let agents read kitchen context, suggest meals that respect dietary safety, update the pantry after cooking, and build a history of what works for your household. Every interaction makes the data richer. Cooking history, preference signals, kitchen awareness = better suggestions next time. All tools work via oAuth and a free scraps.kitchen account.
Machine-readable utilities and datasets for AI agents.
Gateway between LLM agents and world data through eight tools and a bundled endpoint catalog.
U.S. civic data for AI agents: reps, votes, bills, finance, lobbying, cited gov sources. 47 tools.
