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Retirement planner with great wisdom
Roth conversion optimizer · Social Security claiming strategy · Monte Carlo retirement simulator · Python retirement calculator · AI retirement planner · MCP retirement tool · Claude Gemini Cursor Zed VS Code
Owl is an open-source retirement planning tool that helps US retirees answer the hardest questions in retirement income planning: when to claim Social Security, how much to convert to Roth each year, which accounts to withdraw from first, and how to minimize lifetime taxes. It uses mixed-integer linear programming to optimize withdrawal strategies rather than merely simulate them, finding the mathematically best sequence of decisions across all accounts simultaneously.
Users can stress-test their plan with historical back-testing, Monte Carlo simulation with sequence-of-returns risk, or fixed rates derived from historical averages.
Tax optimization — federal + state income tax (all 50 states + DC), LTCG brackets, NIIT, Medicare IRMAA, and ACA premiums all embedded in the optimizer
Account types — taxable, tax-deferred (401k/IRA), Roth, and HSA accounts with full contribution and withdrawal rules
Roth conversions — amounts and timing co-optimized with spending and bequest goals
Value of optimization — compare_to_baseline solves the same plan with and without the strategy (no Roth conversions, Social Security at stated ages, taxable-first withdrawal ordering) and reports the advantage in today's dollars — a mathematical lower bound from the optimizer itself, not a simulation estimate
Explainability — explain_results reads the LP shadow prices to report what each goal and rule costs at the margin, which tax brackets the plan deliberately fills (and why), and the order in which accounts are drawn down. Every recommendation is explained using the mathematics of the optimization itself: the AI interprets and narrates quantities computed by the solver — it does not find the answer
Social Security — own, spousal, and survivor benefits; optional optimization of claiming age (monthly resolution, 62–70)
Pension & SPIA — pension income with survivor fractions; IRA-funded SPIA with optional CPI indexing and joint-and-survivor benefit
Two objectives — maximize net spending subject to a bequest floor, or maximize after-tax bequest subject to a spending floor
Spending profile — flat or smile-curve shape with survivorship factor; optional time-preference discounting to reduce end-of-life back-loading
Asset allocation — user-specified glide path (linear or s-curve) across four asset classes (equities, corporate bonds, T-notes, cash); per-account, per-individual, or household-wide
Stochastic analysis — Monte Carlo with optional longevity risk (mortality tables by sex and category: SSA, VBT, RP-2014, IAM-2012, Pub-2010); spending efficiency frontier tracing the optimal spending vs. shortfall-risk trade-off
Rate models — 17 models including historical replay, bootstrap, VAR, GARCH-DCC, HMM, GMM, and Gaussian copula
AI assistant — MCP server lets Claude Desktop, Claude Code, Gemini CLI, Cursor, Zed, VS Code (Copilot/Cline), and other MCP-compatible AI clients run optimizations, compute probability-of-success frontiers, quantify and explain strategies, and compare scenarios through natural conversation — eighteen tools plus a guided owl_intake interview prompt, with every assumption made for omitted inputs disclosed in the response (assumed_defaults). No TOML files required:
"I'm 65, have $800k in my IRA and $200k taxable, $2,400/month Social Security at 67 — what can I safely spend each year with 90% historical probability of success?"
Self-hosted installs can also enable a built-in Assistant chat page that reads the case open in the app (OWL_ASSISTANT=1); the Connect your AI page in the web UI generates the client configuration either way.
Among open-source retirement planning tools, Owl stands out for the breadth and rigor of its financial modeling. While the full API rewards those willing to invest time, the Streamlit web interface provides an accessible entry point for all users.
There are four ways to run Owl (from easiest to more complex):
Streamlit Hub: Run Owl remotely as hosted on the Streamlit Community Cloud at owlplanner.streamlit.app.
Docker Container: Run Owl locally on your computer using a Docker image. Follow these instructions for using this option.
Self-hosting: Run Owl locally on your computer using Python code and libraries. Follow these instructions to install from the source code and self-host on your own computer.
AI assistant (MCP): Connect Owl as a tool to an AI assistant — Claude Desktop, Claude Code, Gemini CLI, Cursor, Zed, VS Code (Copilot or Cline), or any MCP-compatible client. The AI can discover cases, run optimizations, compute probability-of-success frontiers, and compare scenarios through natural conversation — no TOML files required. Requires a local installation; see info/mcp.md for setup. The Connect your AI page (under Tools in the web UI) generates the copy-paste configuration for Claude Desktop, Claude Code, Cursor, Gemini CLI, VS Code, and Zed.
See CREDITS.md.
Please submit bugs and feature requests through GitHub if you have a GitHub account or directly by email. Or just drop me a line to report your experience with the tool.
This app does not store or forward any information. All data entered is lost after a session is closed. However, you can choose to download selected parts of your own data to your computer before closing the session. These data will be stored strictly on your computer and can be used to reproduce a case at a later time.
The optional self-hosted Assistant page is disabled by default and never available on the hosted app; when you explicitly enable it, your conversation — including case data you ask about — is sent to the AI provider you configure. The optimizer itself always runs locally.
Copyright © 2024-2026 Martin-D. Lacasse and The Owl Authors.
This project is distributed under three separate licenses depending on the type of file:
.py, .sh) is licensed under the
GNU General Public License v3 (see LICENSE)..md, .qmd, .ipynb, .tex) is licensed under the
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 license, CC-BY-NC-SA-4.0
(see LICENSE-docs).assets/ directory — are all rights reserved,
Copyright © 2024-2026 Martin-D. Lacasse. They are not covered by the GPLv3 and
may not be reproduced or modified without permission (see assets/LICENSE).Owl is for educational and research purposes only. Nothing here constitutes financial, tax, or investment advice—consult a qualified professional for decisions specific to your situation.
Code output has been verified with analytical solutions when applicable, and comparative approaches otherwise. Nevertheless, accuracy of results is not guaranteed.
Retirement planner with great wisdom
เครื่องมือ
ยังไม่มีรายการเครื่องมือ เซิร์ฟเวอร์แบบรีโมตจะได้รายการหลังการตรวจสอบสถานะครั้งแรก
FAQ
คัดลอกคอนฟิก stdio สำหรับ Cursor, Claude Desktop, Claude Code หรือ VS Code ได้ในหน้านี้ คอนฟิกนี้ใช้การติดตั้งของผู้เผยแพร่ ไม่ใช่พร็อกซีของ PlugMCP
ระเบียนนี้ไม่ได้ระบุตัวแปรสภาพแวดล้อมที่จำเป็น
Owl ทำงานแบบโลคัลผ่าน stdio
ตรวจสอบล่าสุดเมื่อ 2026-11-13 Retirement planner with great wisdom