Generates secure payment links to book private chauffeur transfers.
Retrieves pricing information for transfer quotes via WordPress API.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MyDriverParis MCP Server Get quote from CDG to Le Bristol for 2 passengers tomorrow at 2pm"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Book premium private chauffeur transfers in Paris and across Europe — directly from AI agents.
Remote endpoint (streamable HTTP, no auth, no API key):
https://mcp-mydriverparis.mydriverparis.workers.dev/mcp
Published on the Official MCP Registry as com.mydriverparis/booking · Smithery · ClawHub skill for OpenClaw.
Tool | Description |
| Exact all-inclusive prices for any transfer, hourly hire or day trip. Returns a |
| Secure Stripe payment link from a |
| VIP airport/station Meet & Greet at fixed prices (CDG, Orly, Gare de Lyon, Gare du Nord), optional transfer combo |
| Fuzzy location ("Le Bristol", "CDG") → canonical address candidates |
| Flight number + date → terminals, scheduled/revised times, status |
| Train number + date → route and times via the official SNCF API (TGV, TER, Intercités, Lyria, Eurostar) |
| Mercedes fleet with passenger/luggage capacities |
| Coverage, airports, stations, policies |
| Full cancellation/refund/modification policy |
All tools return structured errors {code, message, retriable, suggested_action} and carry MCP annotations (title, readOnlyHint, destructiveHint).
An authenticated endpoint (/mcp/private, OAuth 2.1 per-booking tokens) lets agents track, reschedule or cancel an existing booking — see auth.md.
Related MCP server: Uber MCP Server
Fixed all-inclusive price (no hidden extras)
Motorway tolls & fuel included
Meet & Greet with nameboard
Flight & train monitoring
Water, Wi-Fi & USB charging
Free cancellation up to 24h before departure
Use the hosted endpoint — no installation required:
{
"mcpServers": {
"mydriverparis": {
"type": "url",
"url": "https://mcp-mydriverparis.mydriverparis.workers.dev/mcp"
}
}
}Per-platform instructions (Claude, Perplexity, OpenClaw, Claude Code): https://www.mydriverparis.com/book-with-your-ai-agent/
The
src/in this repository is the original stdio implementation, kept for reference. It requires private API keys and is superseded by the hosted endpoint above — production runs on a Cloudflare Worker.
resolve_flight with flight_number="AF1234" → arrival time + terminal (pickup = arrival + 45 min international / +25 min Schengen)
get_quote with pickup/dropoff, pickup_date (dd/mm/yyyy), pickup_time → per-vehicle prices + quote_id
book_ride with quote_id, vehicle_id, passenger details, fresh UUID idempotency_key
Share the returned payment_url — the booking is confirmed only after the customer pays
Full agent documentation: llms-full.txt
Agents can never invent a price — quotes are computed live and locked server-side
Agents can never pay — they receive a Stripe payment link; a human completes it
Geocoding sanity gate rejects implausible routes (GEOCODING_SUSPECT)
Website: https://www.mydriverparis.com
Contact: contact@mydriverparis.com · +33 1 88 33 64 43 (24/7)
MIT — see LICENSE.
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.
| Name | Required | Description | Default |
|---|---|---|---|
| bags | No | Number of bags | |
| price | Yes | Price in EUR from get_quote results (integer) | |
| passengers | No | Number of passengers | |
| vehicle_id | Yes | Vehicle ID from get_quote results | |
| pickup_date | Yes | Pickup date in dd/mm/yyyy format | |
| pickup_time | Yes | Pickup time in HH:MM format | |
| vehicle_name | Yes | Vehicle name from get_quote results | |
| flight_number | No | Flight number for airport pickups (e.g. AF123) | |
| passenger_name | Yes | Full name of the passenger | |
| pickup_address | Yes | Pickup address | |
| dropoff_address | Yes | Drop-off address | |
| passenger_email | Yes | Passenger email for booking confirmation | |
| passenger_phone | Yes | Passenger phone number with country code (e.g. +33612345678) |
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.
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.
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.
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.
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.
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.
Calculate the exact price for a private chauffeur transfer. Returns prices for all available vehicles. Always call this before book_ride to get an accurate quote.
| Name | Required | Description | Default |
|---|---|---|---|
| form_type | No | Booking type: one_way (point-to-point), hourly, or flat (fixed route) | one_way |
| num_hours | No | Number of hours (required if form_type is hourly) | |
| pickup_date | Yes | Pickup date in dd/mm/yyyy format (e.g. '27/03/2026') | |
| pickup_time | Yes | Pickup time in HH:MM format (e.g. '14:00') | |
| step_address | No | Intermediate stop address (optional, for hourly bookings) | |
| pickup_address | Yes | Pickup address (e.g. 'CDG Terminal 2E' or full address) | |
| dropoff_address | Yes | Drop-off address (e.g. 'Hotel Le Bristol, Paris') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals that the tool returns prices for all vehicles and that it should be called before booking, which are key behavioral traits. While it doesn't explicitly state it has no side effects, the verb 'calculate' and the name 'get_quote' strongly imply a non-destructive read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences, each serving a distinct purpose: stating the action, describing the output, and providing usage guidance. It is front-loaded with the most important information and contains no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides the essential context: it returns prices for all vehicles and is a prerequisite for booking. It does not address edge cases or conditional parameter requirements (e.g., num_hours for hourly bookings), but the schema already covers those details, making the description reasonably complete for a simple quote tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage, so the baseline is 3. The description adds no additional parameter-level detail beyond what the schema already provides, so it does not exceed the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the exact price for a private chauffeur transfer and returns prices for all available vehicles. It distinguishes itself from the sibling tool book_ride by positioning this as a pre-booking step, and the mention of 'prices' differentiates it from get_vehicles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs to call this tool before book_ride, providing a clear usage order and alternative. This directly addresses when to use the tool versus a key sibling, fulfilling the requirement for explicit usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get information about MyDriverParis services, coverage areas, airports served, and policies. Use this to answer customer questions about what is included.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. The verb 'Get' implies a read-only operation, and the description lists the scope of information, but it does not explicitly state whether there are side effects, authorization requirements, or how the response is structured.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and followed by a practical use case. Every phrase earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter information lookup tool, the description covers the main topics and the intended use. It lacks explicit detail about the return format or any limitations, but it is otherwise complete enough for the agent's purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and an empty schema, so the description does not need to explain parameter semantics. The baseline score of 4 applies because there are no parameters to document.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves information about MyDriverParis services, coverage areas, airports served, and policies. It distinguishes itself from siblings by focusing on general service information rather than vehicles, quotes, or bookings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to use this tool to answer customer questions about what is included, which provides clear usage context. It does not explicitly mention when not to use it or name alternatives, but the purpose alone is enough to differentiate it from the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all available vehicles with capacity and base rates. Use this to help the customer choose the right vehicle for their trip.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. It accurately indicates a read-only listing operation and specifies the returned data (capacity and base rates). While it does not mention ordering or edge cases, the tool is simple enough that this level of transparency is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the action and resource, and contains no extraneous information. Every word contributes to understanding the tool's purpose and usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (no parameters, no output schema, simple listing), the description is fully complete. It states what the tool does, what data it returns, and when to use it, which is sufficient for an agent to select and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific information, but none is needed since there are no parameters to explain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all available vehicles with their capacity and base rates, using the specific verb 'List' with a resource. This distinguishes it from siblings like get_quote, book_ride, and get_service_info, which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says to use this tool to help the customer choose the right vehicle for their trip, providing clear usage context. It does not mention exclusions or alternative tools, but the context is sufficient to differentiate from the siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0book_rideget_quoteget_service_infoget_vehiclesEach tool serves a distinct purpose: listing vehicles, quoting prices, booking a ride, and providing service info. There is no functional overlap, making it easy for an agent to select the correct tool.
All tool names follow the verb_noun pattern with consistent get_ and book_ prefixes (get_vehicles, get_quote, book_ride, get_service_info). Naming is uniform and predictable.
Four tools is well-scoped for a chauffeur booking server. Each tool is necessary for the core workflow: discover vehicles, get pricing, book, and answer questions.
The booking workflow is complete (vehicles → quote → book), and service info covers typical questions. However, there are no tools for viewing managing existing bookings, which is a minor gap in the domain.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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