Skip to main content
Glama
chaituredd

DoorDash MCP Server

by chaituredd

DoorDash MCP Server

MCP server that wraps DoorDash's Drive API. Lets AI agents (Claude, Cursor, etc.) search restaurants, place delivery orders, and track them in real time.

Comes with built-in mock data so you can try it without DoorDash API credentials.

Architecture

graph TB
    subgraph "MCP Clients"
        C1[Claude Desktop]
        C2[Cursor]
        C3[Claude Code]
    end
    
    subgraph "MCP Server"
        T[Transport - stdio / SSE]
        S[Server Core]
        
        subgraph "Tools"
            RT[Restaurant Tools]
            DT[Delivery Tools]
            TT[Tracking Tools]
            AT[Account Tools]
        end
        
        subgraph "Service Layer"
            MC[Mock Client]
            DC[DoorDash Client]
        end
    end
    
    DD[DoorDash Drive API]
    
    C1 & C2 & C3 --> T
    T --> S
    S --> RT & DT & TT & AT
    RT & DT & TT & AT --> MC
    RT & DT & TT & AT -.->|live mode| DC
    DC --> DD

Quick Start

No API keys needed — mock mode is the default:

git clone https://github.com/chaituredd/doordash-mcp-server.git
cd doordash-mcp-server
npm install && npm run build

The build step prints the MCP client config JSON. Paste it into your Claude Desktop or Cursor settings.

Or with Docker:

docker compose -f docker/docker-compose.yml up

Tools

12 tools across 4 domains:

Tool

What it does

Mock

Live

search_restaurants

Find nearby restaurants

get_menu

Full menu with prices and modifiers

get_restaurant_details

Hours, ratings, delivery info

create_delivery_quote

Fee estimate, valid for 5 min

accept_delivery_quote

Confirm quote → start delivery

create_delivery

Skip the quote, create directly

cancel_delivery

Cancel before pickup

get_delivery_status

Status timeline + ETA

list_active_deliveries

All in-progress deliveries

get_business_info

Business account details

list_stores

Stores under a business

create_store

Register a new store

Configuration

Copy .env.example to .env:

Variable

Required

Default

Description

DOORDASH_API_MODE

No

mock

mock or live

TRANSPORT

No

stdio

stdio or http

PORT

No

3000

Port when using HTTP transport

DOORDASH_DEVELOPER_ID

Live only

From DoorDash Developer Portal

DOORDASH_KEY_ID

Live only

From DoorDash Developer Portal

DOORDASH_SIGNING_SECRET

Live only

From DoorDash Developer Portal

MCP Client Config

Claude Desktop / Claude Code:

{
  "mcpServers": {
    "doordash": {
      "command": "node",
      "args": ["/absolute/path/to/doordash-mcp-server/build/index.js"],
      "env": {
        "DOORDASH_API_MODE": "mock"
      }
    }
  }
}

Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "doordash": {
      "command": "node",
      "args": ["/absolute/path/to/doordash-mcp-server/build/index.js"]
    }
  }
}

Development

npm install          # install deps
npm run dev          # watch mode
npm test             # run tests
npm run test:watch   # tests in watch mode
npm run typecheck    # type checking

Project Layout

src/
├── index.ts          # entry point, transport setup
├── server.ts         # tool/resource/prompt registration
├── config.ts         # env validation (Zod)
├── tools/            # one file per tool domain
├── services/         # DoorDash clients (real + mock)
├── data/             # mock restaurants, menus, deliveries
├── types/
└── utils/            # logger, errors, validation

Live Mode

  1. Sign up at developer.doordash.com (sandbox is free)

  2. Grab your credentials and run:

DOORDASH_API_MODE=live \
DOORDASH_DEVELOPER_ID=your_id \
DOORDASH_KEY_ID=your_key \
DOORDASH_SIGNING_SECRET=your_secret \
npm start

New accounts start in sandbox. Production requires a separate application to DoorDash.

How It Works

Implements the Model Context Protocol spec. AI agents call tools through MCP, the server translates those into DoorDash Drive API requests (or returns mock data), and formats responses for the agent to show the user.

The mock layer is stateful — create a delivery and it'll progress through created → confirmed → enroute_to_pickup → picked_up → enroute_to_dropoff → delivered each time you check status. Makes demos actually useful.

Tech

TypeScript (strict), Node 18+, @modelcontextprotocol/sdk v1.x, Zod for validation, Axios for HTTP, Vitest for tests, GitHub Actions CI, Docker multi-stage build.

Why This Exists

Wanted to learn MCP properly by building something non-trivial with it. DoorDash's Drive API seemed like a good fit since it has a real delivery lifecycle to model. The mock layer turned out to be the most useful part — you can demo the whole flow without any API keys.

License

MIT

-
security - not tested
F
license - not found
-
quality - not tested

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/chaituredd/doordash-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server