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MCP Server

Driive includes a built-in MCP (Model Context Protocol) server that lets AI agents interact with your scheduling data. Instead of building custom API integrations for every AI tool, MCP provides a standardized way for AI assistants to check availability, create appointments, look up contacts, and more — all through a single protocol.

What is the Model Context Protocol?

The Model Context Protocol (MCP) is an open standard for connecting AI agents to external tools and data sources. Think of it as a universal adapter: any AI tool that supports MCP can plug into Driive without custom integration code.

What this means for you:

  • AI assistants like Claude can read and manage your Driive data

  • Voice-to-booking workflows can check availability and create appointments in real time

  • Custom AI agents can automate scheduling tasks on behalf of your team

  • You get a standard, secure interface instead of building one-off API integrations

Use cases

Scenario

How it works

AI scheduling assistant

A customer interacts with a chatbot that checks your real-time availability and books an appointment — no human intervention needed

Voice-to-booking

A customer calls your business, speaks with an AI voice assistant, and the assistant creates the appointment in Driive

Automated appointment management

An AI agent monitors your schedule and proactively reschedules or fills open slots based on rules you define

Internal team assistant

Your dispatcher asks an AI assistant "What's on the schedule for tomorrow?" and gets an instant answer pulled from Driive

Smart lead qualification

An AI agent reviews incoming appointment requests and triages them based on appointment type, location, and availability

Setting up the MCP Server

Step 1: Navigate to the MCP Server page

Go to Developer > MCP Server in the sidebar.

Step 2: Copy your server endpoint URL

The MCP Server page displays your organization's unique endpoint URL. This is the URL your AI agent will connect to. Copy it.

Step 3: Create an API key for authentication

MCP connections are authenticated with an API key. If you don't already have one:

  1. Navigate to Developer > API Keys.

  2. Create a new key with the permissions your AI agent needs (Read for querying data, Write if the agent should create or update records).

  3. Copy the key.

See API Keys for detailed instructions.

Step 4: Configure your AI agent

In your AI tool or agent framework, add Driive as an MCP server using:

  • Endpoint URL — The URL you copied in Step 2

  • API Key — The key you created in Step 3

The exact configuration steps depend on your AI tool. Consult your tool's documentation for how to add an MCP server connection.

Available capabilities

Once connected, your AI agent can use the following capabilities through the MCP server.

Tools

Tools are actions the AI agent can perform:

  • View appointments — Retrieve details for specific appointments or list appointments by date range, status, or assignee

  • Search appointments — Find appointments matching specific criteria

  • Check availability — Query open time slots for a given date range and appointment type

  • Create bookings — Schedule new appointments with customer details, appointment type, and preferred time

  • Manage appointments — Update appointment details, reschedule, or cancel existing bookings

  • Access contacts — Look up customer information, search contacts, and view appointment history

  • Query appointment types — List available services, durations, and team assignments

Prompts

The MCP server also exposes pre-built prompts that help AI agents understand how to interact with your Driive data effectively. These prompts provide context about your organization's appointment types, scheduling rules, and data structure.

Security

MCP connections are secured with the same safeguards as the rest of Driive's developer tools:

  • API key authentication — Every MCP request must include a valid API key

  • Organization-scoped — The AI agent can only access data belonging to your organization

  • Permission-based — The agent's capabilities are limited by the API key's permission level (Read or Write)

  • Audit trail — MCP requests are tracked the same way as API requests, including last-used timestamps on your API key

Security recommendations

  • Use a dedicated API key for your MCP connection — don't share it with other integrations

  • Grant the minimum permissions needed. If the agent only needs to check availability and view appointments, use a Read key

  • Set an expiration date on the API key if the MCP connection is for a specific project or trial

  • Revoke the key immediately if you decommission the AI agent or suspect unauthorized access

Troubleshooting

If your AI agent can't connect to the MCP server or isn't returning expected results:

  • Verify the endpoint URL — Make sure you copied the full URL from the MCP Server page

  • Check the API key — Confirm the key is active, hasn't expired, and has the correct permissions

  • Test with a simple query — Start with a read-only operation (like listing appointment types) to confirm the connection works before trying more advanced actions

  • Check your AI tool's MCP documentation — Configuration varies by tool; make sure the endpoint and authentication are set up correctly

For more detailed troubleshooting, see Troubleshooting Developer Tools.

Next steps

  • API Keys — Create and manage the API key that authenticates your MCP connection

  • Developer Overview — See how MCP fits into Driive's full developer platform

  • Webhooks — Combine MCP with webhooks for a complete integration (e.g., AI agent responds to real-time events)

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