SDKs for Python and JavaScript, a full REST API, webhooks and a playground. Your first restaurant query is two lines of code away.
from menuclaw import MenuClaw mc = MenuClaw(api_key="mc_live_...") # Every dish that contains pork bone broth, under $15 dishes = mc.dish.search( query="ramen with pork bone broth", max_price=15, near="35.6762,139.6503", ) for d in dishes: print(d.name, "-", d.restaurant.name, "-", d.calories, "kcal")
pip install menuclaw
JavaScript SDK · npm i menuclaw
REST / OpenAPI
Full type definitions, autocomplete and runtime validation in Python and TypeScript. Errors surface at compile time, not production.
Per-endpoint latency, error rates and cost in the dashboard. Know exactly what your app is querying and why.
Subscribe to menu changes, price updates and restaurant lifecycle events for the venues you track. No polling.
Free sandbox keys with full graph access on sample data. Test everything before you go to production.
Versioned, backwards-compatible APIs. Breaking changes are announced 6 months ahead with migration guides.
Public Slack, office hours and a docs-driven onboarding flow. Enterprise customers get a named solutions engineer.
import { MenuClaw } from "menuclaw"; const mc = new MenuClaw("mc_live_..."); async function recommend(user) { // 1. Ground the answer in real data const results = await mc.dish.search({ query: user.craving, maxPrice: user.budget, near: user.location, dietary: user.restrictions, }); // 2. Feed structured facts to your LLM return generate({ context: results.map(r => ({ dish: r.name, restaurant: r.restaurant.name, calories: r.calories, allergens: r.allergens, }))}); }
Your assistant answers with real dishes, real restaurants, real prices — retrieved from the graph, not hallucinated.
Allergens and dietary labels propagate through the graph, so every recommendation is constraint-aware.
Webhooks keep tracked restaurants current, so "today's menu" is actually today's menu.
Get a sandbox key, read the quickstart, and ship your first restaurant intelligence feature today.