I built an MCP server that lets AI agents book real hotel rooms (no OTA commission)

Booking.com takes 15-25% commission and owns the customer relationship. I run a small
network of independent establishments in Luxembourg, and I wanted AI agents to be able to
book them directly — machine-native, at the establishment's exact direct price.

So I built Adaga Network — Direct Booking Federation: one MCP endpoint that fans out
to every establishment in the network.

The architecture

Each establishment runs the same open template: an mcp.js module mounted on /mcp inside its existing Express app. No new port, no new service — a pure proxy to the app's own REST API.
The federator (adagasolutions.lu/network/mcp) is a Streamable HTTP stateless MCP server that keeps a registry of tenants and calls their MCP tools in parallel (6s timeout per tenant, dead tenants are skipped and reported).

3 tools cover the whole journey:

Tool	What it does
`network_directory`	Lists every establishment (brand, type, city, slug)
`network_search`	Fan-out live availability + exact total prices, sorted
`network_book`	Creates a REAL booking, hands secure card payment to the human

The payment hand-off is a feature

The agent never touches card data. network_book returns payment instructions; the human
completes a Stripe Checkout; unpaid bookings expire automatically. Booking confirmed only
after payment — and a 409 if the room became unavailable in between.

What I learned writing tool descriptions

The tool description is the #1 selection criterion for agents. After running the tools
through a TDQS audit, the fixes that mattered:

State auth requirements, rate limits and pagination explicitly (mine: none, none, none)
Put the full workflow in the transactional tool's description
Describe every optional input format (phone: international format, extras: integer ids)
Units everywhere: prices in euro cents, dates YYYY-MM-DD, max 30 nights

Distribution

Official MCP Registry: io.github.jeffreyturov-dev/adaga-network
Glama connector with health checks (hourly) — a watchdog pings the endpoint every 10 min
The honest pitch: no OTA commission — the traveler pays the exact direct price, the establishment keeps its customer.

Salons and restaurants join the network next. If you run an independent establishment and
want AI agents to book you directly, the onboarding template takes 2-4 hours.