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@striderlabs/mcp-opentable

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@striderlabs/mcp-opentable

Restaurant discovery and autonomous reservations via OpenTable. Let your AI agent search dining options, check real-time availability, and book tables. Persistent session management for travel agents and personal AI assistants. Production-ready MCP server

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@striderlabs/mcp-opentable

Book restaurant reservations via OpenTable 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 your Claude Desktop config:
{
  "mcpServers": {
    "opentable": {
      "command": "npx",
      "args": ["-y", "@striderlabs/mcp-opentable"]
    }
  }
}
  • Restart Claude.
  • Tell Claude: "Book a table for 4 at an Italian restaurant for 7 PM tonight"

Your agent can now book reservations. That's it.

Installation (NPM)

npm install @striderlabs/mcp-opentable

Or with npx directly:

npx @striderlabs/mcp-opentable

Features

  • 🔍 Search restaurants by cuisine, location, and rating
  • Check availability for specific times and party sizes
  • 📅 Make reservations with one-click confirmation
  • 📝 View booking history and manage reservations
  • 🏷️ Filter by price, cuisine, and dining style
  • 🔐 Persistent sessions - stay logged in across restarts
  • 🔄 Automatic MFA - handles multi-factor authentication
  • 📱 Per-user credentials - encrypted session storage

Tested & Compatible

ComponentVersionStatus
MCP SDK^1.0.0
Node.js18+
Claude DesktopLatest
Claude (API)claude-3.5-sonnet+
Anthropic SDK^0.20+

Metrics

  • Weekly downloads: 187 (Apr 10-17, 2026) — Top restaurant connector (+467% growth)
  • Status: ✅ Live in production
  • Reliability: 85%+ task completion rate
  • Discovery: npm, Claude Plugins, mcpservers.org, ClawHub, PulseMCP

Available Elsewhere

How It Works

For Agents

Your agent can use these capabilities:

// Search for restaurants
restaurants = search_restaurants({
  location: "San Francisco, CA",
  cuisine: "Italian",
  price_range: "$$",
  date: "2026-04-15",
  party_size: 4,
  time: "19:00"
})

// Get detailed restaurant info
details = get_restaurant_details({
  restaurant_id: "ristorante-milano-sf"
})

// Check availability
availability = check_availability({
  restaurant_id: "ristorante-milano-sf",
  party_size: 4,
  date: "2026-04-15",
  time: "19:00"
})

// Make a reservation
booking = make_reservation({
  restaurant_id: "ristorante-milano-sf",
  party_size: 4,
  date: "2026-04-15",
  time: "19:00",
  special_requests: "Window seat if possible"
})

// View your reservations
reservations = get_my_reservations()

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 OpenTable changes)
  • Fallback paths for failures
  • 24/7 monitoring + alerting

Configuration

Environment Variables

# Optional: Use a specific OpenTable account
OPENTABLE_EMAIL=your-email@example.com
OPENTABLE_PASSWORD=your-password  # Highly recommend using .env file

Self-Hosted

# Clone the repo
git clone https://github.com/striderlabsdev/mcp-opentable
cd mcp-opentable

# 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 OpenTable, because OpenTable doesn't have a comprehensive public API for reservations. Here's why that's safe and reliable:

  • User-controlled: Your agent only accesses your own OpenTable account
  • Session-based: We store your login session securely, not your password
  • Change-aware: We detect OpenTable UI changes and alert immediately
  • Fingerprinting: We use realistic browser profiles to avoid bot detection
  • Rate-limited: We respect OpenTable's infrastructure with appropriate delays

Security

  • Credentials stored encrypted in your local .env or 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 filters, integrations, 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.

GitHub | Website | Discord

Keywords

mcp

FAQs

Package last updated on 17 Jun 2026

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