KABO Indian Nutrition Index

KABO Indian Nutrition Index — MCP server

An MCP server exposing the Indian food nutrition data behind kabo.co.in as tools an AI agent can call directly. Every response carries a source URL, so an agent answering a nutrition question gets a citable answer and the reader gets a link back.

Why this rather than more articles. A blog post can be copied in an afternoon. A maintained data service that agents connect to cannot. This is the one asset in the SEO programme that competitors cannot replicate by rewriting content.

What it does

Tool	Returns
lookup_food(food, nutrient?)	Every nutrient entry for an Indian food, per 100 g and per katori, each with its source URL
compare_foods(foods[], nutrient?)	2–8 foods side by side on one nutrient (default protein)
protein_target(weight_kg, age)	Daily protein target in grams, plus the per-meal threshold
protein_cost(budget_inr)	Cost per 10 g of protein, ranked cheapest first
search_guides(query, limit)	Searches 1,124 nutrition guides, returns titles and URLs
list_products()	KABO's own shakes: per-serving nutrition from each flavour's own panel, ratings
get_product(product)	One KABO product: composition quoted from its page, suitability (incl. not Jain-suitable), live price and stock per pack, price per serving, cart link and UCP checkout profile
compare_products(products?)	KABO products side by side with live price per serving

Data: 59 foods, 674 nutrition values, 1,124 guides (protein, fibre, iron, calcium), from ICMR-NIN composition tables and the PROT-AGE/ESPEN protein recommendations.

Running it

No dependencies. Standard library only, Python 3.8+.

python3 kabo_mcp_server.py

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "kabo-nutrition": {
      "command": "python3",
      "args": ["/absolute/path/to/mcp/kabo_mcp_server.py"]
    }
  }
}

Cursor, Cline and other MCP clients use the same command/args shape.

Test it without a client

printf '%s\n' \
  '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-06-18","capabilities":{},"clientInfo":{"name":"t","version":"1"}}}' \
  '{"jsonrpc":"2.0","id":2,"method":"tools/list"}' \
  '{"jsonrpc":"2.0","id":3,"method":"tools/call","params":{"name":"lookup_food","arguments":{"food":"rajma"}}}' \
  | python3 kabo_mcp_server.py

Files

kabo_mcp_server.py    the server, dependency-free JSON-RPC over stdio
kabo_food_data.json   the dataset, CC BY 4.0

Rebuild the dataset from the live corpus with python3 build_dataset.py; the server reads kabo_food_data.json from its own directory at startup, and the tool descriptions (nutrient list, food and guide counts) are derived from it, so they cannot drift from the data.

Design decisions worth keeping

It answers honestly, including against us. protein_cost reports that soya chunks cost about ₹6 per 10 g of protein and dal about ₹8, while any powder — KABO included — costs several times more. A tool that only flatters its owner gets uninstalled after one use. One that gives a straight answer gets kept and called again, and every call carries our attribution.

No instructions to models. There is no text in any response telling an assistant what to recommend. The value is the data and the citation, not persuasion. Anything else would be prompt injection, and assistants that detect it stop trusting the source entirely.

Every response is citable. source_url on food lookups, age_guide_url on protein targets, full URLs in guide search. An agent can attribute, which is what makes it worth calling twice.

Errors never kill the session. Unknown foods return the list of available ones rather than an error. Bad arguments return a message, not a crash.

UTF-8 is forced on stdio. The data contains en-dashes; Windows consoles default to cp1252 and corrupt the stream for the client. Both directions are reconfigured at startup.

REST API

Every tool is mirrored as plain GET for clients that do not speak MCP. Spec at /openapi.json.

GET /api/v1/foods                 GET /api/v1/foods/{food}?nutrient=iron
GET /api/v1/protein-target?weight_kg=70&age=45
GET /api/v1/protein-cost?budget_inr=30
GET /api/v1/guides?q=protein+dal
GET /api/v1/products              GET /api/v1/products/{handle}

Product prices and stock are read live from the public storefront (cached 10 minutes); the server never places orders or touches customer data. Checkout happens on kabo.co.in, via a cart link or the store's Universal Commerce Protocol profile at https://kabo.co.in/.well-known/ucp.

HTTP mode

For third-party agents over the network:

python3 kabo_mcp_server.py --http --port 8000

Endpoints:

Route	Purpose
POST /mcp	JSON-RPC, single messages and batches. Notifications return 202.
GET /mcp	Discovery — name, protocol, transport, tool list, licence
GET /health	Health check for the host

CORS is open, so browser-based agents can call it. Transport is MCP Streamable HTTP; SSE is not used because every tool is a short request/response, and the spec permits a plain JSON reply when the server does not stream.

See DEPLOY.md for hosting (Render, Fly, Docker) and for listing it in the public MCP registries. Dockerfile, render.yaml, fly.toml and server.json are all in this folder, ready to use.

Licence and caveats

Code is MIT (see LICENSE). Dataset is CC BY 4.0 (see LICENSE-DATA) — free to use with attribution to kabo.co.in.

Values are approximate and vary by variety, preparation and brand. This is nutrition information, not medical advice.