Both touch restaurants. Loop is a place-data layer for AI agents — structured facts, freshness signals, live verification, and a feedback channel. OpenTable's API is a reservation platform for partner restaurants — live booking slots, not place discovery.
| Feature | Loop | OpenTable API |
|---|---|---|
| Designed for | ✓AI agents — place discovery, verification, feedback | Reservation booking at partner restaurants |
| Protocol | ✓MCP + REST | REST only |
| Output format | ✓Typed JSON per vertical (cuisine, price_band, dietary flags, etc.) | Availability slots and booking confirmation data |
| Freshness signals | ✓observed_at + confidence score on every record | None — no per-record freshness metadata |
| Availability labeling | Explicit inferred: true until verified | Live reservation slots for OpenTable partners |
| Feedback loop | ✓report() mutates record confidence and freshness | None — read-only for affiliate integrators |
| Live verify | ✓verify() re-checks a specific record on demand | None |
| Agent setup time | ✓One URL in any MCP client — no code | Apply for partner access, write wrapper code, handle auth |
| Access | ✓Free tier — no application, no approval | Partnership application and approval required |
| Reservation booking | Not supported — place data and verification only | Live booking at partner restaurants |
| Coverage | Restaurants & salons, Kreuzberg Berlin (582 merchants; expanding by demand) | Global — partner restaurants only |
| Open data attribution | ✓ODbL (OpenStreetMap) + Apache 2.0 (Foursquare OS) | Proprietary — OpenTable ToS restrictions |
| Out-of-coverage response | ✓Explicit honest error with suggested_action | Empty results for non-partner restaurants |
For a concierge or travel agent: use Loopto discover and verify the right restaurant (search by cuisine + dietary flags, verify it's currently open, report outcome after the visit). Use OpenTableto check reservation slots and book once the agent has picked the right place. Loop answers “which restaurant?”, OpenTable answers “when can we book?”
// Step 1 — Loop: discover the right restaurant search({ query: "outdoor dinner, vegetarian-friendly, Kreuzberg", location: "Kreuzberg, Berlin" }) // → up to 8 ranked records with cuisine[], vegan, outdoor_seating, confidence // Step 2 — Loop: verify before recommending verify({ result_id: "m_1042", claim: "open for dinner tonight" }) // → latest_observation + confidence score // Step 3 — OpenTable: check reservation slots // (via OpenTable partner API — requires partnership approval) // GET /availability?restaurantId=...&date=...&partySize=2 // Step 4 — Loop: report after the visit report({ result_token: "<token from get_details>", outcome: "correct" // correct · wrong · booked · closed · other })
Use Loop when you're building an AI agent that needs to discover, verify, or learn from restaurant data. Loop speaks MCP natively, returns typed JSON with freshness signals and dietary/cuisine metadata, and has a report() action that closes the feedback loop. It covers any restaurant in Kreuzberg Berlin — not just partner listings.
Use OpenTable's API when your agent needs to make or check reservations at restaurants already on the OpenTable platform. OpenTable excels at surfacing live availability slots and driving booking flows — tasks Loop does not perform.
Yes — they solve different problems and can complement each other. Loop finds and verifies the right restaurant (is it open, does it have outdoor seating, is the data fresh?). OpenTable checks whether a table is available and books it. A concierge agent could call Loop's search() and verify() first, then hand off to OpenTable for the booking step.
One MCP endpoint. Four tools. Real-time local business data for AI agents. https://stayinloop.dev/mcp — free tier, no credit card.