Rihla

io.github.leojg由 GitHub 账号 leojg 发布v0.1.0更新于 Oct 27, 2026

Flexible multi-leg, multi-airport flight search - cheapest valid combination across an itinerary.

概览

AI 生成的概览

Rihla 是一个本地 MCP 服务器,用于灵活的多段、多机场航班搜索,为整条行程定价并给出最便宜的有效组合。

可以做什么
  • 把地名解析为 IATA 机场代码,并给出附近备选机场,且不消耗搜索配额
  • 按灵活机场、出发时间窗和停留时长搜索多段行程,返回排序后的最便宜组合
  • 标注每段航班的价格来源,区分参考价与可预订票价,并在部分航段无法定价时返回部分结果
  • 为排序后的行程提供预订链接
适用场景
适合规划包含多段航程、多个可选机场或弹性日期的旅行,希望得到整趟行程最便宜的组合而非逐段比价时使用。也适合离线演示,因为它无需密钥即可使用确定性的模拟数据运行。
运行要求
本地 Python 3.10 及以上进程,从 PyPI 安装(rihla-mcp,可用 uvx 运行),通过 stdio 通信。获取实时价格需要 TRAVELPAYOUTS_TOKEN 中的 Travelpayouts Data API 令牌,可选提供 SERPAPI_KEY 中的 SerpApi 密钥;RIHLA_PROFILE 用于选择 local、hosted 或 mock 数据源。未配置密钥时回退到离线模拟数据。使用实时数据源需要网络访问。
安装前请注意
从环境变量读取两个 API 凭据:TRAVELPAYOUTS_TOKEN 和 SERPAPI_KEY。SerpApi 免费额度有限(每月 250 次搜索),search_trip 会消耗该额度,因此应先确认机场。README 提醒不要从公开托管实例提供 SerpApi,因为它会抓取 Google。Travelpayouts 的价格为参考价而非实时票价;该服务器只读,不进行预订或支付。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Rihla,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

Rihla

Rihla (رحلة), "the journey." Named for Ibn Battuta's 14th-century travelogue — the record of history's farthest-traveling explorer, who left Tangier for Mecca and kept going for 29 years and 75,000 miles.

Flexible multi-leg, multi-airport flight search that finds the cheapest route across an entire itinerary — available as a CLI and as an MCP server for AI agents.

Consumer flight sites price one leg at a time. Rihla treats the whole trip as a single optimization problem:

"Leave Montevideo — or Buenos Aires, it's a ferry ride away — around September 15 for Europe. Stay 20–30 days, then Japan for 15, then home. What's the cheapest combination?"

That query has three legs, flexible airports on both ends of each, a flexible departure window, and stay-duration constraints linking the legs. Rihla prices each leg's date×airport grid once, then finds the cheapest valid combinations in pure local compute — so even a 3–4 leg flexible query costs only a handful of API calls.

1. 1,297 USD   (44 days door-to-door)     MVD -> AMS  2026-09-08  $    383  [mock, cached]  AA AA127     FRA -> NRT  2026-10-07  $    481  [mock, cached]  KL KL411     HND -> EZE  2026-10-22  $    433  [mock, cached]  AZ AZ933
2. 1,308 USD   (44 days door-to-door)     MVD -> AMS  2026-09-14  $    446  [mock, cached]  AA AA127     ...

Note the airport substitution at work: it enters Europe through Amsterdam, leaves from Frankfurt, and flies home into Buenos Aires — each leg independently picks the cheapest airport pair from its sets.

Quick start

Requires Python ≥ 3.10.

bash
pip install rihla            # CLIpip install "rihla[mcp]"     # CLI + MCP server

Runs offline out of the box (no keys needed — a deterministic mock data source):

bash
RIHLA_PROFILE=mock rihla                # the canonical demo trip aboverihla examples/queries/canonical.json   # same trip, from a query filerihla -i                                # build a query interactively

For live prices, copy .env.example to .env and add at least a Travelpayouts token (free). See Data sources.

Writing a query

A query is a small JSON file: your origin airports, the ordered stops, a departure window for the first leg, and how long to stay at each stop. Downstream date windows are derived — you never hand-compute "if I leave Sep 15 and stay 20–30 days, when do I fly to Tokyo?"

json
{  "origins": ["MVD", "EZE", "AEP"],  "stops": ["EUROPE", ["NRT", "HND"], "MVD_AREA"],  "earliest": "2026-09-08",  "latest": "2026-09-22",  "stays": [[20, 30], [15, 15]],  "date_step": 3,  "top": 5}
  • origins — IATA codes tried as one origin set; the cheapest wins per date.
  • stops — each stop is a region name or a list of IATA codes. Built-in regions: EUROPE (MAD, BCN, LIS, CDG, FCO, AMS, FRA), TOKYO (NRT, HND), MVD_AREA (MVD, EZE, AEP). Make the last stop your origin set to fly home.
  • earliest / latest — the departure window for the first leg only.
  • stays — [min, max] nights at each intermediate stop (len(stays) == len(stops) - 1).
  • date_step — sample every N days across date windows (coarser = fewer API calls).
  • top — how many ranked combinations to return.
  • currency — optional ISO 4217 code (default USD).

rihla -i walks you through these questions and prints the resulting JSON to save for reuse. Add --links to any run to show booking URLs.

Reading results

Rihla is honest about data quality rather than pretending everything is bookable:

  • Each flight is tagged with its source, and cached when the price is indicative (Travelpayouts data is aggregated search history, not a live fare) versus a real, bookable fare (SerpApi / Google Flights).
  • If some legs can't be priced (thin routes are real — cached sources have gaps), you get a partial result over the legs that were found, never a silently wrong total.
  • For unpriced legs, Rihla shows the nearest cached fares outside your departure window — a hint to shift or widen dates.

Ranking is price-only in v0.1. Open-jaw within a region is allowed by default (enter Europe at one city, leave from another); the cost of repositioning inside the region is not modeled.

Data sources & profiles

SourceRoleCostNotes
Travelpayouts / AviasalesPrimaryFreeCached, redistribution-licensed. A month of prices per call, so the call budget stays tiny. Prices indicative; coverage follows route popularity.
SerpApi (Google Flights)Fill250 free searches/mo (BYO key)Real bookable fares; fills routes Travelpayouts misses. Only spent on uncovered routes.
MockOffline—Deterministic fake prices for development and demos.

Configure via .env (see .env.example) or environment variables: TRAVELPAYOUTS_TOKEN, SERPAPI_KEY, and RIHLA_PROFILE:

  • local (default) — every source whose key is set, including SerpApi.
  • hosted — redistribution-licensed sources only (SerpApi disabled: it scrapes Google, so do not serve it from a public hosted instance).
  • mock — force the offline fetcher, no network.

With no keys set, Rihla falls back to the mock source and says so.

MCP server

Rihla ships an MCP server (stdio) so agents like Claude can run trip searches:

bash
pip install "rihla[mcp]"claude mcp add rihla -- rihla-mcp        # Claude Code

or in any MCP client config:

json
{  "mcpServers": {    "rihla": {      "command": "rihla-mcp",      "env": {        "TRAVELPAYOUTS_TOKEN": "your-token",        "SERPAPI_KEY": "your-key"      }    }  }}

(The server also loads a .env from its working directory, so env is optional if you run it from a checkout.)

It exposes two read-only tools with an enforced etiquette:

  1. resolve_airports — the agent proposes IATA codes for the traveler's named places; Rihla validates and enriches them (nearby alternatives included). Cheap and quota-free.
  2. search_trip — the priced, quota-limited search. Tool descriptions instruct the agent to get the traveler's explicit confirmation of the airports before spending quota here.

mcp-name: io.github.leojg/rihla

How it works

Leg prices are independent — the MVD→Europe fare doesn't depend on the Tokyo dates. So Rihla fetches each leg's date×airport grid once, then enumerates valid date combinations (respecting the stay constraints) entirely in memory. The combinatorial explosion lives in local compute, not in API calls.

core.py            data model + the pure optimizer (no I/O)fetchers/          PriceFetcher protocol: Mock / Travelpayouts / SerpApi + mergeplaces.py          airport sets / regionsapi.py             search_trip: serializable query in, result dict outcli.py             thin CLI over search_tripmcp_server.py      thin MCP wrapper over the same seam

Adding a data source (Duffel, Kiwi, …) is one more class implementing a one-method protocol: quote(origin, dest, day) -> Quote.

Scope (v0.1): flight search only — no lodging, no booking or payments, single adult, one cabin. Search returns booking links, never handles the transaction.

Development

bash
git clone https://github.com/leojg/rihla && cd rihlapip install -e ".[dev,mcp]"pytest              # offline, no keys neededruff check .

License

Licensed under the Apache License 2.0 — see LICENSE.

来源:README.md,提交 24a35e4

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v0.1.0最新Sep 16, 2026

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