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DoorDash MCP Server

An MCP (Model Context Protocol) server that lets AI agents search restaurants, browse menus, compare prices, and manage your DoorDash cart — all without opening a browser or wasting tokens on HTML parsing.

How It Works

Instead of using a browser-based AI agent (which eats context and tokens parsing HTML), this MCP server runs a lightweight background browser that handles authentication and API calls. Your AI agent gets clean JSON — no HTML, no screenshots, no wasted tokens.

Under the hood, it uses DoorDash's internal GraphQL API (reverse-engineered from web traffic) via a Playwright browser instance that maintains your session.

Features

Tool

Description

login_check

Check if your DoorDash session is active

search_restaurants

Search restaurants and food by keyword

get_store_menu

Get full menu with prices, deals, and badges

add_to_cart

Add items to your cart

remove_from_cart

Remove items from cart

list_carts

View all active carts

order_history

Get recent order history

Deals and promotions (Buy 1 Get 1 Free, DashPass offers, etc.) are surfaced in both search results and menu items.

Setup

1. Install

git clone <this-repo>
cd doordash-mcp
npm install
npx playwright install chromium

2. Configure Email

cp .env.example .env

Edit .env and set your DoorDash account email:

DOORDASH_EMAIL=your-email@example.com

3. Login (one-time)

node login.js

This opens a browser, sends an OTP to your email/phone, and saves the session. You only need to do this once (or when your session expires).

On headless Linux: The script auto-starts a virtual display via Xvfb. Make sure xvfb is installed (sudo apt install xvfb).

4. Add to Claude Code

Add to ~/.claude/settings.json:

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

Restart Claude Code to pick up the new server.

Usage

Once configured, just talk to your AI agent naturally:

  • "Search for biryani near me"

  • "Show me the Pizza Hut menu"

  • "What's the cheapest dosa at Thanjai Restaurant?"

  • "Add 2 Masala Dosas to my cart"

  • "What did I order last time?"

  • "Find me a burger place with deals"

How the Spy Tool Works

Want to discover new endpoints or debug? The spy.js script opens a browser and logs all DoorDash API traffic as you browse:

node spy.js

Browse DoorDash normally — search, view menus, add to cart. All API calls get logged to logs/api-calls.jsonl. Close the browser when done.

Architecture

AI Agent  ──(MCP stdio)──>  mcp-server.js  ──(GraphQL via Playwright)──>  DoorDash API
                                 │
                            browser-data/    (persistent session cookies)
  • No headless HTTP: Cloudflare blocks plain HTTP requests. The server uses a real browser (positioned off-screen on macOS, or via Xvfb on Linux)

  • Persistent session: Login once, the browser profile in browser-data/ keeps your cookies alive

  • Minimal tokens: AI agents get structured JSON, never HTML

Platform Notes

Platform

How it runs

macOS

Browser window positioned off-screen (-32000, -32000)

Linux with display

Same as macOS

Linux headless (SSH)

Auto-starts Xvfb virtual display

Disclaimer

This project reverse-engineers DoorDash's internal web APIs for personal use. It is not affiliated with, endorsed by, or connected to DoorDash in any way. Use at your own risk — endpoints may change without notice, and automated access may violate DoorDash's Terms of Service.

License

MIT

Install Server
A
security – no known vulnerabilities
F
license - not found
A
quality - confirmed to work

Resources

Looking for Admin?

Admins can modify the Dockerfile, update the server description, and track usage metrics. If you are the server author, to access the admin panel.

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