Rihla

io.github.leojgPublished by GitHub account leojgv0.1.0Updated Oct 27, 2026

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

Overview

AI-generated overview

Rihla is a local MCP server for flexible multi-leg, multi-airport flight search that prices a whole itinerary and returns the cheapest valid combinations.

What you can do
  • Resolve place names to IATA airport codes, with nearby alternatives, without using search quota
  • Search a multi-leg trip across flexible airports, departure windows and stay durations, returning ranked cheapest combinations
  • Show each flight's price source and flag indicative versus bookable fares, plus partial results when legs cannot be priced
  • Return booking links for the ranked itineraries
When to use it
Useful when planning trips with several legs, flexible airports or flexible dates and you want the cheapest overall combination rather than leg-by-leg prices. Also handy for offline demos, since it runs on deterministic mock data without keys.
Requirements
Local Python 3.10+ process, installed from PyPI (rihla-mcp, runnable with uvx) over stdio. Live prices need a Travelpayouts Data API token in TRAVELPAYOUTS_TOKEN and optionally a SerpApi key in SERPAPI_KEY; RIHLA_PROFILE selects local, hosted or mock sources. Without keys it falls back to offline mock data. Network access is needed for live sources.
Before you install
Two API credentials are read from the environment: TRAVELPAYOUTS_TOKEN and SERPAPI_KEY. SerpApi has a limited free quota (250 searches per month) and search_trip spends it, so confirm airports first. The README warns not to serve SerpApi from a public hosted instance because it scrapes Google. Prices from Travelpayouts are indicative, not live fares; the server is read-only and does not book or pay.

Installation

In SourceWeft

  1. Open Rihla in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

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.

Source: README.md at commit 24a35e4

Tools

0
SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

1
  1. v0.1.0LatestSep 16, 2026

Score

50% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 days25 pts

    Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.

  • Auth declared10 pts

    Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.

  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts