Indian Food Nutrition MCP runs on your own machine — the client starts it, so there is no endpoint to ping. 36 installs a week from npm. Last commit 12 Jun 2026.
Indian-accurate nutrition logging for your AI: IFCT 2017 + USDA, by text or photo.
We read the source, 21 h ago · rules 3dff92dd89df
What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.
.prepare(`SELECT ${COLUMNS.join(", ")} FROM meal_entries ORDER BY logged_at ASC, id ASC`)
Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.
We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.
This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.
claude mcp add indian-food-nutrition-mcp -- npx -y indian-food-nutrition-mcp
{
"mcpServers": {
"indian-food-nutrition-mcp": {
"args": [
"-y",
"indian-food-nutrition-mcp"
],
"command": "npx"
}
}
}
[mcp_servers.indian-food-nutrition-mcp]
command = "npx"
args = ["-y", "indian-food-nutrition-mcp"]
{
"mcpServers": {
"indian-food-nutrition-mcp": {
"args": [
"-y",
"indian-food-nutrition-mcp"
],
"command": "npx"
}
}
}
{
"mcpServers": {
"indian-food-nutrition-mcp": {
"args": [
"-y",
"indian-food-nutrition-mcp"
],
"command": "npx"
}
}
}
Food photo recognition, nutrition search, meal logging and glucose prediction for health apps
Food logging, nutrition summaries, and meal photo calorie and macro estimates.
Nutrition tracking by Dieta.ai. Read your food log with macros (calories, protein, carbs, fat, fiber
AI bookkeeping for small business. Create invoices, log expenses, and check P&L by voice or text.
One permissioned folder your team and your AI agents both log into.
AI assistant integration for Leaf — track books, log reading sessions, and manage your library.
Timestamped audit log for every AI conversation — stored locally in SQLite, owned by you.
Structured execution trace and span logging for AI agents
Answers built from our own checks of this server.