A
licenseNot graded
qualityA
maintenanceEnables flight search and fare calendar exploration by interacting with Google Flights' API, supporting detailed filters for origin, destination, dates, cabin class, airlines, and more.
5,092 PyPI
3,234
MIT
cheapdates-mcp
by afgoes
cheapdates
Günstigste Daten, um eine Route zu fliegen, direkt von Google Flights. CLI + MCP-Server.
Warum es das gibt: Der Preiskalender von Google (GetCalendarGraph) wird pro Anfrage von BotGuard signiert, daher liefert jeder reine HTTP-Client (fli dates, google-flights-mcp, …) seit Mitte 2026 leere Ergebnisse. cheapdates hat zwei Backends:
graph — steuert headless Chromium zur Routenseite, öffnet Price graph und liest den Kalender, den die Seite selbst erhält. Ein Aufruf ≈ 60 Abflugdaten, einfach oder hin- und zurück. ~3 s pro 60 Tage.
sweep — eine fast-flights Suche pro Datum, kein Browser. ~0,5 s pro Datum mit 4 Workern; verrät auch die Fluggesellschaft.
auto (Standard) verwendet graph, wenn Playwright + Chromium installiert sind, sonst sweep; wenn graph fehlschlägt, fällt es auf sweep zurück.
Installation
git clone https://github.com/afgoes/cheapdates.git && cd cheapdates && uv sync # see INSTALL.md
python -m playwright install chromium # for the graph backendRelated MCP server: google-flights-mcp
CLI
cheapdates JFK LHR 2026-10-01 2026-11-30 # one-way
cheapdates JFK LHR 2026-10-01 2026-11-30 -r 7 # round trip, 7 nights
cheapdates JFK LHR 2026-10-01 2026-11-30 --nonstop --json
cheapdates JFK LHR 2026-10-01 2026-11-30 -b sweep # force fast-flightsMCP (Claude Code)
claude mcp add cheapdates -- uv run --directory /path/to/cheapdates cheapdates-mcpTool: cheapest_dates_tool(origin, destination, start, end, trip_length?, currency?, nonstop?, seat?, backend?).
Python
import datetime as dt
from cheapdates import cheapest_dates
r = cheapest_dates("JFK", "LHR", dt.date(2026,10,1), dt.date(2026,11,30), trip_length=7)
print(r.cheapest)Einschränkungen
Reverse-engineered; Google kann die Seite oder Antwort jederzeit ändern. Der Parser ist mit Fixtures getestet (pytest), und das graph-Backend fällt bei Fehlern auf sweep zurück.
Available Tools
1 toolcheapest_dates_toolA
Cheapest fare for each departure date between start and end (YYYY-MM-DD) on origin→destination.
trip_length: None for one-way, or N for a round trip returning N days after departure. Returns {cheapest, days:[{depart, ret, price, airlines}], backend, warnings}. The 'graph' backend reads Google Flights' own price calendar (fast, ~60 days per call); 'sweep' searches each date individually. 'auto' picks graph when a browser is available.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| end | Yes | ||
| seat | No | economy | |
| start | Yes | ||
| origin | Yes | ||
| backend | No | auto | |
| nonstop | No | ||
| currency | No | USD | |
| destination | Yes | ||
| trip_length | No |
TDQS
A3.6/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the behavior of different backends (graph vs sweep vs auto) and mentions speed implications, which is useful. However, it does not disclose any data limitations, rate limits, or potential variability in results, which would be helpful for a tool using different search backends.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loaded with the main purpose, and provides structured information about trip_length and backend behavior. It uses bullet-like structure within paragraphs effectively, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 9 parameters and no output schema, the description provides a solid overview but lacks detailed parameter explanations and behavioral notes. It covers the essential usage and return format but could be more complete by describing the meaning of the warning field, typical use cases, and edge cases like date boundaries.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 9 parameters but the description does not explicitly map each parameter beyond trip_length and backend. Schema description coverage is 0%, so the description must compensate, but it only explains a couple of parameters. The return structure is described, but parameter semantics for origin, destination, start, end, seat, nonstop, currency are left to the schema, which has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds the cheapest fare for each departure date over a date range for a given route, distinguishing it from typical one-off price lookup tools. It specifies input format and return structure, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the trip_length parameter (one-way vs round trip) and backend options, but does not explicitly state when to prefer this tool over alternatives. Since no sibling tools are provided, we cannot evaluate differentiation, but the description does give context on how to use different backends.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
v0.1.0- First observed
cheapest_dates_tool
TDQS
A3.7/5.0
Scored across 1 tool
Disambiguation5/5
With only one tool, there is zero ambiguity—an agent cannot confuse it with any other. The tool's purpose is clearly described.
Naming Consistency4/5
The single tool name 'cheapest_dates_tool' is descriptive but uses a bare noun with a redundant 'tool' suffix rather than a verb_noun pattern. Since there is no set of names to compare, it is not inconsistent, but the naming style is slightly unconventional.
Tool Count3/5
The server exposes only one tool, which is at the borderline of being too thin. While the tool encapsulates a coherent function, a larger set (e.g., specific date lookup, fare alerts) could better justify a dedicated MCP server.
Completeness4/5
The tool fully covers the stated purpose—finding cheapest fares across a date range. It supports one-way and round-trip queries, provides pricing and airline details, and handles backend selection automatically. Minor gaps like booking integration or fare alerts are outside its shown scope.
Maintenance
ActivityMaintained
ResponsivenessNo issues
Related MCP Connectors
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Google Flights prices for any route and date: round trips, cabins, stops, airlines, cheapest dates.
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