awardmath-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@awardmath-mcpFind an economy award from LAX to HNL with 60k Amex points"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
AwardMath MCP server
awardmath-mcp connects AI assistants to the public AwardMath API through the Model Context Protocol.
AwardMath is the travel points optimizer. You provide your points balances and a travel goal. A deterministic solver searches a versioned graph of transfer ratios and award charts, then returns up to three verified, explainable booking plans.
The math is enumeration and scoring over published charts. An LLM can parse your question and explain the results, but it never chooses or optimizes the plans.
This repository contains the MCP server and a free data snapshot under data/. The server is read-only. It requires no API key, login, or subscription, and it does not scrape airline sites.
Tools
The server exposes three tools.
Tool | What it does |
| Lists tracked and spendable programs |
| Returns up to three plans |
| Structures wallet text |
list_programs
list_programs returns every program AwardMath tracks and identifies which program IDs a solve can spend today.
Spendable programs include award programs with priced charts and bank currencies that transfer into one of those programs. This distinction prevents an assistant from asking the solver to spend a balance that has no path to a priced award.
solve_award_trip
solve_award_trip searches for plans that fit your wallet, origins, destinations, cabins, traveler count, and cash cap.
A successful response contains up to three plans with:
Exact transfer steps
Total points required
Priced fees
If no plan fits, the response includes no_plan_reasons. These identify the constraint that failed instead of filling the gap with a guessed route or price.
parse_wallet
parse_wallet turns free text into structured balances.
For example:
250k Amex, 80k ChaseClear balances become program IDs and amounts. Ambiguous phrases are surfaced for clarification rather than assigned to a program by guesswork.
Setup
You can run the server directly from GitHub or install it from a clone.
Claude Code
claude mcp add awardmath -- uvx --from git+https://github.com/DanCastHub/awardmath-mcp awardmath-mcpClaude Desktop or another JSON-configured MCP client
{
"mcpServers": {
"awardmath": {
"command": "uvx",
"args": ["--from", "git+https://github.com/DanCastHub/awardmath-mcp", "awardmath-mcp"]
}
}
}From a clone
pip install -e .
awardmath-mcpNo API key or AwardMath account is required.
Example
Ask your assistant for a priced plan using the balances you already have.
You: I have 60,000 Amex Membership Rewards points. Find one economy seat from LAX to HNL.
Assistant: As of 2026-08-23, the best-priced plan used 16,000 Qatar Avios for the seat, funded through an Amex transfer at 1:1. The result includes the exact transfer steps, total points, and fees. It does not confirm that a seat is available.
That result is dated because transfer ratios and award prices change. Run a new solve, confirm the award seat, and re-check the transfer terms before moving points.
The dataset
The data/ directory provides a dated slice of the rewards graph and worked solver output.
data/transfer-ratios-current.csv
This file contains 109 bank-to-program transfer edges from eight source currencies, as observed on 2026-08-23.
Each row represents the most recent observation AwardMath had verified against a program page or corroborated across independent sources. Editorial claims that had not been verified were excluded.
Columns include:
Transfer ratio
Fees
Transfer time, where observed
Verification status
Date observed
Ratios change. Treat every row as valid only as of its observed date, then re-check the program before transferring points.
data/sample-solved-plans.json
This file contains five scenarios run through the live solver on 2026-08-23.
Four scenarios produced plans. They include:
LAX to HNL in economy with 60,000 Amex Membership Rewards points
SFO to HND in business with 100,000 Amex Membership Rewards points, priced through ANA at 82,500 points
One scenario is deliberately empty. The YVR to DXB business search shows how the solver responds when the graph cannot price a route. It names the missing graph coverage instead of inventing a plan.
What is not included
The dataset is a snapshot, not the full AwardMath product.
The versioned history behind it stays at awardmath.com. That history tracks ratios and charts over time and supports price-history and book-now-or-wait calls. It is not included in this repository.
What this will not do
The server does not check live award-seat availability.
Plans are priced from published award charts and transfer relationships. A route can be mathematically valid while having no seats available on your dates.
Before you move any points:
Confirm the award space through Seats.aero, PointsYeah, or the airline.
Check the points price and cash charges with the booking program.
Re-check the transfer ratio and terms.
Transfers are irreversible. Do not transfer because the solver found a priced path. Transfer only after you have confirmed that the seat can be booked.
AwardMath verifies the math. You confirm the seat.
Licenses
The code is licensed under the MIT License.
The files under data/ are licensed under CC BY 4.0. Use this attribution with a link:
Data: AwardMath
Sources:
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