FlightFinder
A Python client for searching flights and hotels without API keys, providing an MCP server for AI agents to search flights, hotels, and plan trips.
README
FlightFinder
A Python client for searching flights and hotels. No API keys required.
- Flights: Kiwi/Skypicker GraphQL API
- Hotels: Xotelo API (TripAdvisor data)
Features
-
Flight Search
- One-way and round-trip search
- "Anywhere" destination search - find the cheapest flights to any destination
- Location/airport code lookup
- Async support with
AsyncFlightFinder
-
Hotel Search
- Search hotels in 30+ major cities worldwide
- Filter by price, rating, accommodation type
- Price ranges and review summaries
-
Combined Trip Planning
- Search flights and hotels together
- Estimated trip cost calculation
-
AI Agent Integration
- MCP server for Claude and other AI agents
- CLI skill for Vercel AI SDK agents
-
Notifications
- Discord webhook integration
- Background monitoring service
-
Developer Features
- Response caching with configurable TTL
- Retry logic with exponential backoff
- Rate limit handling
- Multiple output formats (table, JSON, CSV)
- Interactive REPL mode
Installation
# Install from PyPI
pip install flightfinder
# Or with MCP server support
pip install flightfinder[mcp]
# Or with HTTP MCP server support
pip install flightfinder[mcp-http]
# Or install all extras
pip install flightfinder[all]
MCP HTTP Server Security
The HTTP MCP server binds to 127.0.0.1 by default and keeps DNS rebinding
protection enabled. Local development does not require a token:
flightfinder-mcp-http
Remote or tunneled use must opt in with an API token plus explicit Host and Origin allowlists. Wildcard hosts and origins are rejected.
export FLIGHTFINDER_MCP_API_TOKEN="$(openssl rand -hex 32)"
flightfinder-mcp-http \
--host 0.0.0.0 \
--allowed-host flightfinder.example.com \
--allowed-origin https://trusted-client.example.com
HTTP clients must send one of:
Authorization: Bearer <token>
X-FlightFinder-API-Token: <token>
Development Installation
# Clone the repository
git clone https://github.com/wolfgangschoenberger/flightfinder.git
cd flightfinder
# Using uv (recommended)
uv sync
# Or using pip
python3 -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
Quick Start
Python API
from flightfinder import FlightFinder
from datetime import date, timedelta
# Search for flights
with FlightFinder() as finder:
# One-way search
flights = finder.search_flights(
origin="SFO",
destination="LAX",
departure_from=date.today() + timedelta(days=30),
max_stops=1,
limit=10,
)
for flight in flights:
print(f"${flight.price:.0f} - {flight.origin} → {flight.destination}")
print(f" {flight.departure_time.strftime('%b %d %H:%M')} | {flight.duration_formatted}")
print(f" {flight.stops_label} | {', '.join(flight.carriers)}")
# Round-trip search
roundtrips = finder.search_roundtrip(
origin="SFO",
destination="anywhere", # Find cheapest destinations
departure_from=date.today() + timedelta(days=30),
min_days=7,
max_days=14,
max_price=500,
)
for rt in roundtrips:
print(f"${rt.price:.0f} - {rt.origin} ⇄ {rt.destination}")
print(f" {rt.trip_days} days | {rt.destination_city}")
# Location search
locations = finder.find_location("San Francisco")
for loc in locations:
print(f"{loc.id} - {loc.name} ({loc.type})")
Async API
import asyncio
from flightfinder import AsyncFlightFinder
from datetime import date, timedelta
async def search_multiple_origins():
async with AsyncFlightFinder() as finder:
# Search from multiple airports concurrently
results = await finder.search_multiple_origins(
origins=["SFO", "OAK", "SJC"],
destination="LAX",
departure_from=date.today() + timedelta(days=30),
)
for origin, flights in results.items():
print(f"\nFrom {origin}:")
for flight in flights[:3]:
print(f" ${flight.price:.0f} - {flight.duration_formatted}")
asyncio.run(search_multiple_origins())
CLI Usage
# One-way search
flights search SFO -d LAX --days 30 --max-stops 1
# Round-trip search
flights roundtrip SFO -d anywhere --min-days 7 --max-days 14 --max-price 500
# Search to anywhere
flights search SFO --days 30 --format json -o flights.json
# Location search
flights location "San Francisco" --type AIRPORT
# Export to CSV
flights search SFO -d LAX --format csv -o results.csv
# Interactive mode
flights repl
CLI Commands
flights search
Search for one-way flights.
flights search <origin> [options]
Options:
-d, --destination Destination (default: anywhere)
--days Days from now to start search (default: 30)
--window Search window in days (default: 7)
--max-stops Maximum stops (default: 1)
--max-price Maximum price filter
--min-price Minimum price filter
--limit Number of results (default: 20)
--sort Sort by: PRICE, DURATION, QUALITY (default: PRICE)
--cabin Cabin class: ECONOMY, PREMIUM_ECONOMY, BUSINESS, FIRST
--format Output format: table, json, csv (default: table)
-o, --output Output file path
-v, --verbose Enable verbose logging
flights roundtrip
Search for round-trip flights.
flights roundtrip <origin> [options]
Options:
(same as search, plus:)
--min-days Minimum trip duration (default: 7)
--max-days Maximum trip duration (default: 14)
--return-from Days from now for earliest return
--return-to Days from now for latest return
flights location
Search for airport/city codes.
flights location <query> [options]
Options:
--type Filter by: AIRPORT, CITY, COUNTRY
--limit Maximum results (default: 10)
--format Output format: table, json, csv
flights repl
Start interactive mode.
flights repl
# In REPL:
flights> search SFO LAX
flights> roundtrip SFO anywhere
flights> location Tokyo
flights> cache
flights> clear
flights> quit
Configuration
FlightFinder can be configured via file or environment variables.
Config File
Create ~/.flightfinder/config.json or ./flightfinder.json:
{
"api": {
"timeout": 30.0,
"max_retries": 3,
"retry_delay": 1.0,
"retry_backoff": 2.0
},
"cache": {
"enabled": true,
"ttl_seconds": 300,
"max_size": 100
},
"search_defaults": {
"adults": 1,
"cabin_class": "ECONOMY",
"max_stops": 2,
"sort_by": "PRICE",
"limit": 100
}
}
Environment Variables
export FLIGHTFINDER_API_URL="https://api.skypicker.com/umbrella/v2/graphql"
export FLIGHTFINDER_TIMEOUT=30
export FLIGHTFINDER_MAX_RETRIES=3
export FLIGHTFINDER_CACHE_ENABLED=true
export FLIGHTFINDER_CACHE_TTL=300
export FLIGHTFINDER_CONFIG=/path/to/config.json
Programmatic Configuration
from flightfinder import FlightFinder, Config
config = Config()
config.api.timeout = 60.0
config.cache.enabled = True
config.cache.ttl_seconds = 600
finder = FlightFinder(config=config)
Deal Alerts
Set up price alerts for routes you want to monitor:
from flightfinder.alerts import DealAlertManager, PriceAlert, format_alert_match
manager = DealAlertManager()
# Add an alert
alert = PriceAlert(
origin="SFO",
destination="LAX",
max_price=150,
round_trip=True,
min_days=7,
max_days=14,
name="LA Weekend Trip",
)
manager.add_alert(alert)
# Set callback for matches
def on_deal(match):
print(format_alert_match(match))
manager.on_match = on_deal
# Check alerts
matches = manager.check_alerts(days_ahead=30, window=14)
print(f"Found {len(matches)} deals!")
# Alerts are persisted to ~/.flightfinder/alerts.json
manager.close()
Data Models
Flight
flight.price # float: Price in USD
flight.origin # str: Origin airport code
flight.destination # str: Destination airport code
flight.departure_time # datetime: Departure time
flight.arrival_time # datetime: Arrival time
flight.duration_minutes # int: Total flight duration
flight.stops # int: Number of stops
flight.carriers # list[str]: Airline names
flight.segments # list[Segment]: Individual flight segments
flight.deep_link # str: Booking URL
flight.duration_formatted # str: "2h 30m"
flight.stops_label # str: "Direct", "1 stop", "2 stops"
RoundTrip
rt.price # float: Total round-trip price
rt.outbound # Flight: Outbound flight
rt.inbound # Flight: Return flight
rt.trip_days # int: Days between flights
rt.destination_city # str: Destination city name
rt.destination_country # str: Country code
rt.checked_bag_price # float: First checked bag price
rt.price_with_bag # float: Total with bag
rt.is_domestic # bool: True if within US
rt.is_international # bool: True if outside US
Location
loc.id # str: Location ID / airport code
loc.name # str: Full name
loc.type # str: AIRPORT, CITY, COUNTRY
loc.city # str: City name
loc.country # str: Country name
loc.country_code # str: Country code
loc.latitude # float: GPS latitude
loc.longitude # float: GPS longitude
Testing
# Run all tests
pytest
# Run with coverage
pytest --cov=flightfinder
# Run specific test file
pytest tests/test_client.py -v
# Run specific test
pytest tests/test_models.py::TestFlight::test_duration_formatted -v
Project Structure
flightfinder/
├── src/flightfinder/
│ ├── __init__.py # Package exports
│ ├── client.py # Sync FlightFinder client
│ ├── async_client.py # Async FlightFinder client
│ ├── models.py # Data models (Flight, Location, etc.)
│ ├── queries.py # GraphQL query definitions
│ ├── config.py # Configuration management
│ ├── cache.py # Response caching
│ ├── exceptions.py # Custom exceptions
│ ├── alerts.py # Deal alert system
│ └── cli.py # Command-line interface
├── tests/ # Test suite
├── examples/ # Example scripts
└── pyproject.toml # Project configuration
Hotel Search
Python API
from flightfinder import HotelFinder
with HotelFinder() as finder:
# Search hotels in a city
results = finder.search_hotels(
location="new york", # or "tokyo", "paris", etc.
limit=20,
min_price=100,
max_price=300,
min_rating=4.0,
)
for hotel in results.hotels:
print(f"{hotel.name} - ${hotel.min_price}/night")
print(f" Rating: {hotel.rating}/5 ({hotel.review_count} reviews)")
print(f" Type: {hotel.accommodation_type}")
CLI Usage
# Search hotels
flights hotels "new york" --max-price 200 --min-rating 4.0
# List supported cities
flights hotel-locations
# Export to JSON
flights hotels tokyo --format json -o hotels.json
Combined Trip Planning
# Search flights + hotels together
flights trip SFO tokyo --days 30 --nights 7
# With price filters
flights trip LAX "new york" --max-price 400 --max-hotel-price 150
# Python API
from flightfinder import FlightFinder, HotelFinder
from datetime import date, timedelta
# Search flights
with FlightFinder() as flight_finder:
flights = flight_finder.search_roundtrip(
origin="SFO",
destination="NRT", # Tokyo Narita
departure_from=date.today() + timedelta(days=30),
min_days=7,
max_days=10,
)
# Search hotels
with HotelFinder() as hotel_finder:
hotels = hotel_finder.search_hotels("tokyo", limit=10)
# Calculate trip cost
min_flight = min(f.price for f in flights)
min_hotel = min(h.min_price for h in hotels.hotels if h.min_price)
total = min_flight + (min_hotel * 7)
print(f"Estimated 7-night trip: ${total:.0f}")
Discord Integration
Send search results to Discord via webhook:
# One-time search with Discord notification
flights search SFO -d LAX --discord
# Round-trip with Discord notification
flights roundtrip SFO -d tokyo --min-days 7 --max-days 14 --discord
# Trip planning with Discord
flights trip SFO tokyo --nights 7 --discord
Configuration
Add your Discord webhook URL to ~/.flightfinder/config.json:
{
"discord": {
"webhook_url": "https://discord.com/api/webhooks/YOUR_WEBHOOK_ID/YOUR_WEBHOOK_TOKEN"
}
}
Python API
from flightfinder import DiscordNotifier, FlightFinder
# Search and send to Discord
with FlightFinder() as finder:
flights = finder.search_flights("SFO", "LAX", ...)
with DiscordNotifier(webhook_url="https://...") as notifier:
notifier.send_search_results("SFO", "LAX", flights)
MCP Server (AI Agent Integration)
FlightFinder includes an MCP (Model Context Protocol) server for integration with Claude and other AI agents.
Available Tools
| Tool | Description |
|---|---|
search_flights |
One-way flight search |
search_roundtrip |
Round-trip search with trip duration |
find_location |
Airport/city code lookup |
search_hotels |
Hotel search by location |
search_trip |
Combined flight + hotel search |
Usage with Claude Code
Add to your Claude Code MCP configuration (.claude/settings.local.json):
{
"mcpServers": {
"flightfinder": {
"command": "flights",
"args": ["mcp-server"]
}
}
}
Or use the provided mcp.json:
{
"mcpServers": {
"flightfinder": {
"command": "python",
"args": ["-m", "flightfinder.mcp_server"]
}
}
}
Running the MCP Server
# Install with MCP support
pip install flightfinder[mcp]
# Run the MCP server (stdio transport)
flights mcp-server
# Or run directly
python -m flightfinder.mcp_server
API Notes
- No authentication required (public API)
- Content providers: KIWI, FRESH, KAYAK
- Sort options: PRICE, QUALITY, DURATION, POPULARITY
- Cabin classes: ECONOMY, PREMIUM_ECONOMY, BUSINESS, FIRST
- For "anywhere" searches, pass the literal string
"anywhere"as destination
Contributing
See CONTRIBUTING.md for development setup and guidelines.
License
MIT License - see LICENSE for details.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。