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mydriver-paris

MyDriverParis MCP Server

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book_ride

Generate a payment link to book a private chauffeur transfer. Once payment succeeds, the booking is automatically created and a chauffeur assigned.

Instructions

Create a payment link to book a private chauffeur transfer. The customer will receive a Stripe Checkout URL to complete payment. Once paid, the booking is automatically created and a chauffeur is assigned. Always call get_quote first to get the correct price and vehicle_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bagsNoNumber of bags
priceYesPrice in EUR from get_quote results (integer)
passengersNoNumber of passengers
vehicle_idYesVehicle ID from get_quote results
pickup_dateYesPickup date in dd/mm/yyyy format
pickup_timeYesPickup time in HH:MM format
vehicle_nameYesVehicle name from get_quote results
flight_numberNoFlight number for airport pickups (e.g. AF123)
passenger_nameYesFull name of the passenger
pickup_addressYesPickup address
dropoff_addressYesDrop-off address
passenger_emailYesPassenger email for booking confirmation
passenger_phoneYesPassenger phone number with country code (e.g. +33612345678)
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description fully discloses the workflow: it creates a Stripe Checkout URL, and upon payment the booking is automatically created and a chauffeur assigned. This explains the mutation and consequential effects of the call, going beyond a simple 'creates a booking' statement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, front-loaded with the main purpose. Each sentence adds essential context: the action, the payment flow, the post-payment outcome, and the required prerequisite. There is no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 13 parameters and no output schema, the description sufficiently explains the end-to-end process: what the tool does, what the customer sees (Stripe URL), what happens after payment (booking creation, chauffeur assignment), and the mandatory first step (get_quote). This is complete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds minimal parameter-specific detail, but it does reinforce that vehicle_id and price come from get_quote, which aligns with the schema's mention. No further semantic enhancement is provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: 'Create a payment link to book a private chauffeur transfer.' Clearly differentiates from sibling tools like get_quote and get_vehicles by focusing on the booking action rather than price or vehicle listing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states the required precondition: 'Always call get_quote first to get the correct price and vehicle_id.' This guides the agent to use get_quote before executing book_ride, clarifying tool orchestration and avoiding incorrect usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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