@Striderlabs/ Doordash
БесплатноНе проверенAI agents can order DoorDash food delivery: search restaurants, browse menus, add items to cart, place orders, and track delivery in real-time.
Описание
AI agents can order DoorDash food delivery: search restaurants, browse menus, add items to cart, place orders, and track delivery in real-time.
README
Order food delivery via DoorDash using AI agents
npm MCP Registry Claude Desktop License: MIT
Part of Strider Labs — action execution for personal AI agents.
Get Started in 2 Minutes
For Claude Desktop Users
- 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.
Installation (NPM)
npm install @striderlabs/mcp-doordash
Or with npx directly:
npx @striderlabs/mcp-doordash
Features
- 🔍 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
Tested & Compatible
| Component | Version | Status |
|---|---|---|
| MCP SDK | ^1.0.0 | ✅ |
| Node.js | 18+ | ✅ |
| Claude Desktop | Latest | ✅ |
| Claude (API) | claude-3.5-sonnet+ | ✅ |
| Anthropic SDK | ^0.20+ | ✅ |
Metrics
- 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
Available Elsewhere
- 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
How It Works
For Agents
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 })
Session Management
- Each user has encrypted, persistent credentials
- Automatic OAuth token refresh
- MFA handling (SMS/email)
- Sessions survive agent restarts
Reliability
- 85%+ task completion rate
- Automated UI change detection (connectors update when DoorDash changes)
- Fallback paths for failures
- 24/7 monitoring + alerting
Configuration
Environment Variables
# Optional: Use a specific DoorDash account
[email protected]
DOORDASH_PASSWORD=your-password # Highly recommend using .env file
Self-Hosted
# 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:3000
Architecture
How We Connect
This 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
Security
- 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
Support
Contributing
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.
License
MIT — Free to use, modify, and distribute. See LICENSE for details.
Built by Strider Labs — Making AI agents actually useful.
Установка @Striderlabs/ Doordash
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/markswendsen-code/mcp-doordashFAQ
@Striderlabs/ Doordash MCP бесплатный?
Да, @Striderlabs/ Doordash MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для @Striderlabs/ Doordash?
Нет, @Striderlabs/ Doordash работает без API-ключей и переменных окружения.
@Striderlabs/ Doordash — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить @Striderlabs/ Doordash в Claude Desktop, Claude Code или Cursor?
Открой @Striderlabs/ Doordash на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
Похожие MCP
Fetch
Web content fetching and conversion for efficient LLM usage.
AWS KB Retrieval
Retrieval from AWS Knowledge Base using Bedrock Agent Runtime.
автор: modelcontextprotocolSpring AI MCP Server
Provides auto-configuration for setting up an MCP server in Spring Boot applications.
llm-analysis-assistant
A very streamlined mcp client that supports calling and monitoring stdio/sse/streamableHttp, and can also view request responses through the /logs page. It also
автор: xuzexin-hzCompare @Striderlabs/ Doordash with
Не уверен что выбрать?
Найди свой стек за 60 секунд
Автор?
Embed-бейдж для README
Похожее
Все в категории ai
