Order food delivery via DoorDash using AI agents
Part of Strider Labs — action execution for personal AI agents.
- Add this to
~/.openclaw/config.jsonor your Claude Desktop config:
{
"mcpServers": {
"doordash": {
"command": "npx",
"args": ["-y", "@striderlabs/mcp-doordash"]
}
}
}- Restart Claude.
- Tell Claude: "Order Thai food from nearby for delivery today"
Your agent can now place orders. That's it.
npm install @striderlabs/mcp-doordashOr with npx directly:
npx @striderlabs/mcp-doordash- 🔍 Search restaurants by name, cuisine, or food type
- 📜 Browse menus with full item details and prices
- 🛒 Add to cart with quantity and special instructions
- 💳 Place orders with confirmation step
- 📍 Track orders with real-time status updates
- 🔐 Persistent sessions - stay logged in across restarts
- 🔄 Automatic MFA - handles multi-factor authentication
- 📱 Per-user credentials - encrypted session storage
| Component | Version | Status |
|---|---|---|
| MCP SDK | ^1.0.0 | ✅ |
| Node.js | 18+ | ✅ |
| Claude Desktop | Latest | ✅ |
| Claude (API) | claude-3.5-sonnet+ | ✅ |
| Anthropic SDK | ^0.20+ | ✅ |
- Weekly downloads: 395 (Apr 10-17, 2026) — #1 Strider Labs connector (+24% growth)
- Status: ✅ Live in production
- Reliability: 85%+ task completion rate
- Discovery: npm, Claude Plugins, mcpservers.org, ClawHub, PulseMCP
- npm: npmjs.com/@striderlabs/mcp-doordash
- Claude Plugins: Search "Strider Labs" in Claude
- mcpservers.org: Strider Labs DoorDash
- Full Strider Labs: github.com/striderlabsdev/striderlabs
Your agent can use these capabilities:
// Search for restaurants
restaurants = search_restaurants({
location: "San Francisco, CA",
cuisine: "Thai",
max_delivery_time: 30
})
// Browse a restaurant's menu
menu = get_restaurant_menu({
restaurant_id: "thai-place-downtown",
search: "Pad Thai"
})
// Place an order
order = place_order({
restaurant_id: "thai-place-downtown",
items: [
{ item_id: "pad_thai", quantity: 1 },
{ item_id: "spring_rolls", quantity: 2 }
],
delivery_address: "123 Main St, San Francisco, CA",
special_instructions: "Extra lime on the side"
})
// Track delivery
status = track_order({ order_id: order.order_id })- Each user has encrypted, persistent credentials
- Automatic OAuth token refresh
- MFA handling (SMS/email)
- Sessions survive agent restarts
- 85%+ task completion rate
- Automated UI change detection (connectors update when DoorDash changes)
- Fallback paths for failures
- 24/7 monitoring + alerting
# Optional: Use a specific DoorDash account
DOORDASH_EMAIL=your-email@example.com
DOORDASH_PASSWORD=your-password # Highly recommend using .env file# Clone the repo
git clone https://github.com/striderlabsdev/mcp-doordash
cd mcp-doordash
# Install dependencies
npm install
# Start the server
npm start
# Your agent can now connect to localhost:3000This connector uses browser automation (Playwright) to interact with DoorDash, because DoorDash doesn't have a public API. Here's why that's safe and reliable:
- User-controlled: Your agent only accesses your own DoorDash account
- Session-based: We store your login session securely, not your password
- Change-aware: We detect DoorDash UI changes and alert immediately
- Fingerprinting: We use realistic browser profiles to avoid bot detection
- Rate-limited: We respect DoorDash's infrastructure with appropriate delays
- Credentials stored encrypted in your local
.envor secure vault - Sessions isolated per user
- No data sent to third parties
- MIT Licensed — audit the code yourself
We welcome contributions! Areas of interest:
- Bug reports and fixes
- Feature requests (new restaurants, cuisines, etc.)
- Performance improvements
- Documentation enhancements
See CONTRIBUTING.md for guidelines.
MIT — Free to use, modify, and distribute. See LICENSE for details.
Built by Strider Labs — Making AI agents actually useful.