DoorDash Drive MCP. Manage last-mile logistics, quote routes, and track jobs.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
DoorDash Drive equips your AI agent to run full last-mile logistics. You can request price quotes for new deliveries, create jobs on demand, list current shipments, track dasher locations in real time, or audit overall fulfillment success rates.
What your AI agents can do
Cancel active delivery
Stops a delivery job that hasn't been picked up yet.
Create new delivery
Requests and starts a new DoorDash delivery service run.
Get delivery details
Fetches the full, real-time status for a single, specific job ID.
Get an instant price and estimated time-of-arrival for any route.
Create a brand new delivery request using specific addresses.
Retrieve detailed, real-time status updates and locations for any existing job.
Pull a list of recent or currently running jobs across your account.
Get high-level summaries on delivery volume and success rates.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
DoorDash Drive: 10 Tools for Logistics Operations
These tools let you programmatically handle the entire lifecycle of a DoorDash delivery job—from pricing estimates to final status reports.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using DoorDash Drive on Vinkius019d7588cancel active delivery
Stops a delivery job that hasn't been picked up yet.
019d7588create new delivery
Requests and starts a new DoorDash delivery service run.
019d7588get delivery details
Fetches the full, real-time status for a single, specific job ID.
019d7588get delivery quote
Calculates and retrieves the price and estimated time for a potential route.
019d7588get doordash developer metadata
Retrieves basic information about the DoorDash developer account used to connect the MCP.
019d7588list doordash deliveries
Shows a list of all delivery jobs, both active and completed, in your account.
019d7588list in progress deliveries
Identifies only the deliveries that are currently moving or out for drop-off.
019d7588list latest deliveries
Pulls a list of the most recently created or updated delivery jobs.
019d7588quick delivery volume audit
Generates a summary report detailing overall activity and success rates for deliveries.
019d7588search deliveries by external id
Finds a specific delivery using an ID you provide that isn't the standard DoorDash job ID.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with DoorDash Drive, then connect any of our 4,800+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,800+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DoorDash Drive. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Checking delivery status today is a mess of tabs and spreadsheets.
Right now, figuring out if a package is late involves opening your main dashboard to see all recent activity. Then you might have to open a second tab to check the dasher's live location map, cross-referencing that data with an internal ticket number in a third system just to get one clear answer.
With this MCP, you tell your agent exactly what job ID or external reference number you're worried about. The agent pulls all that scattered information—status, ETA, dasher location—and gives it back as one clean, immediate reply.
Get a full audit of delivery volume with quick_delivery_volume_audit.
Before this MCP, generating an activity summary meant running separate reports for successful jobs, failed pickups, and canceled attempts. This took manual data pulling and merging across several reporting interfaces.
Now, you ask the agent to run `quick_delivery_volume_audit`. It runs the necessary checks and spits out a single summary of success rates and total volume immediately. You get actionable metrics in seconds.
What you can do with this MCP connector
Manage the entire lifecycle of local deliveries without leaving your chat window. Instead of checking multiple websites and manually logging statuses into a sheet, you tell your agent what needs doing—from figuring out if a delivery is even possible to tracking it until it's dropped off. You can ask for an instant price quote between any two points or immediately request a new drop-off job.
As the shipment moves, the MCP tracks dasher locations and updates ETAs automatically. Because logistics data touches so many parts of business operations, you can use this MCP to build automations that connect DoorDash tracking to your CRM records or inventory systems, all through one AI agent running on Vinkius.
This means every single status update, call, and action is logged in a cryptographically signed audit trail, giving you complete visibility into how the delivery happened.
019d7588-e1fc-7272-a2bc-bf882354ba07 
How DoorDash Drive MCP Works
- 1 Connect the DoorDash Drive MCP to your AI client using your Developer ID, Key ID, and Signing Secret.
- 2 Tell your agent what you need. For example: 'What's the price from 123 Main St to 456 Oak Ave?'
- 3 The agent executes the necessary call and returns the data—a price quote, a list of active jobs, or confirmation that the delivery was created.
The bottom line is: you talk to your agent like talking to an employee who can pull real-time data from DoorDash’s system instantly.
Who Is DoorDash Drive MCP For?
Logistics managers and operations leads use this MCP when they need immediate visibility into complex, moving physical assets. It's for the person tired of switching between three different dashboards just to confirm if a job is running late.
Needs to monitor fulfillment volumes and identify any bottlenecks by listing all active and recent shipments.
Uses this MCP constantly to get quotes for new routes or check the current status of a critical, time-sensitive delivery job.
Needs to pull specific details and ETAs for a customer who is calling in about an existing order number.
What Changes When You Connect
- Stop guessing on delivery costs. Use the
get_delivery_quotetool to get instant pricing and ETA for any potential route before committing resources. - Need an urgent status check? Instead of navigating through dashboards, ask your agent to use
get_delivery_detailsto pull real-time tracking information for a single job ID. - Audit your performance without logging in manually. Use
quick_delivery_volume_auditto get high-level stats on success rates and overall volume instantly. - When a job is done, but you need a record of it? The
list_doordash_deliveriestool pulls all recent activity into one place for review. - Handling emergencies? You can use
search_deliveries_by_external_idto find a delivery using your own internal reference number, skipping the DoorDash job ID lookup.
Real-World Use Cases
A customer calls asking where their package is.
The agent uses search_deliveries_by_external_id with the order number provided by the client. It then reports that delivery status and ETA directly, resolving the call without human intervention.
A new drop-off is needed in an unfamiliar zone.
The ops manager asks for a quote between two coordinates. The agent runs get_delivery_quote, determines the cost and time, allowing them to decide if it's viable before creating the job.
A planned delivery job was cancelled by the client.
Instead of having to find the active job ID in a list, the agent uses cancel_active_delivery with the provided reference number and confirms the cancellation immediately.
End-of-day review of fulfillment capacity.
The logistics lead runs list_in_progress_deliveries to see everything currently moving. They then use quick_delivery_volume_audit to get the total success rate for the day.
The Tradeoffs
Listing all deliveries and manually filtering.
A user runs list_doordash_deliveries, gets a giant list, and then has to read through 20 entries just to find the jobs that are currently moving.
→
You should use list_in_progress_deliveries instead. That tool filters the dataset for you, giving only the active jobs right away.
Trying to create a job without knowing if it's possible.
The user immediately calls create_new_delivery with coordinates that are outside the service zone and gets an immediate error message.
→
First, run get_delivery_quote. This checks feasibility and returns pricing/ETAs upfront. If the quote is good, then you call create_new_delivery.
Searching by a generic description of a job.
The user asks: 'Find the delivery for John Smith that was supposed to happen yesterday.' The system fails because it needs a specific ID or reference.
→
You have two options. Use list_latest_deliveries if the job happened recently, or use search_deliveries_by_external_id with your own known customer/reference ID.
When It Fits, When It Doesn't
Use this MCP if you need to manage a delivery from initial quote through final audit. Specifically, run it when you need to compare the cost of a potential route (get_delivery_quote) against the reality of an active job's status (get_delivery_details). Don't use it if your goal is simply to view static historical data; then, pull that information from dedicated record-keeping databases. If you only need general tracking without quoting or creation capability, list_doordash_deliveries works. But remember: this MCP lets you act on the logistics—it doesn't just read history.
Common Questions About DoorDash Drive MCP
How do I find an old delivery job using search_deliveries_by_external_id? +
You provide your own external reference ID to the agent, and it searches through the system for that specific record. This is faster than scrolling through all your listed deliveries.
Can I use get_delivery_quote before creating a job? +
Yes, this is exactly what get_delivery_quote does. It lets you test the viability and cost of a route without committing to an actual delivery order.
What's the difference between list_doordash_deliveries and list_in_progress_deliveries? +
The list_doordash_deliveries tool shows everything in your account, active or finished. The other tool only returns jobs that are currently moving or out for drop-off.
Is there a way to cancel an old delivery using cancel_active_delivery? +
You must use the job ID associated with the active order. If the job has already been picked up, you won't be able to cancel it.
How do I verify my connection details using `get_doordash_developer_metadata`? +
It retrieves basic information about your authenticated account. This confirms that the MCP has access to the necessary credentials and verifies the scope of data it can interact with.
When should I use `get_delivery_details` instead of trying to cancel a delivery? +
Always check the current status first. Use get_delivery_details to confirm if the order is already 'In Transit' or 'Picked Up', as cancellation will fail in those states.
What specific data does `quick_delivery_volume_audit` return about my operations? +
This tool provides high-level summaries of success rates and overall delivery activity. It helps managers gauge operational health without needing individual order IDs.
After running `create_new_delivery`, how do I monitor the actual dasher assignment status? +
Run list_in_progress_deliveries immediately after creation. This will show if a dasher has been assigned and provide real-time location updates until the delivery is completed.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.