Optionsahoy Mcp

OptionsAhoy MCP Server

[](https://glama.ai/mcp/servers/AlvisoOculus/optionsahoy-mcp) [](https://www.npmjs.com/package/optionsahoy-mcp) [](https://mcpsafe.io/scan/pubfast497de7f7a5466f2a414a) [](https://optionsahoy.com/for-agents)

Independently verified by third parties. Glama: third-party MCP-directory quality score (tool docs, behavior, completeness). · npm: published with build provenance, a signed SLSA attestation that this package was built from this repo by GitHub Actions (verify with npm audit signatures). · MCPSafe: independent 5-model-consensus security scan (AIVSS), Grade A with zero findings.

Validated against trusted sources (checks we run ourselves, against references we do not control, and that you can reproduce). Computation: every 2026 federal tax constant matches its IRS Rev. Proc. 2025-32 / Internal Revenue Code value, and 14 worked federal cases (ordinary income, long-term capital gains, and the Alternative Minimum Tax including the incentive stock option bargain element) reproduce to the cent against the independently-maintained PSL Tax-Calculator, a tax model we did not write. State income tax is cross-checked the same way: 16 cases across California, New York, New Jersey, Pennsylvania, and Massachusetts reproduce to the cent against OpenTaxSolver, an independent state tax engine we also did not write. The headline answer is recomputed live in your browser.

Tested and hardened. Input safety: requests are validated against the published schema; bad inputs return a clear 400 with the offending field named, never a crash or a wrong number, and the live API is re-checked by a robustness suite after every deploy. · Test suite: the calculation engine is covered by more than a thousand automated tests across the federal and 50-state tax logic, AMT credit recovery, and option pricing; a failing test blocks the release.

Live usage: MCP calls over the last 30 days, served straight from the server's own telemetry (/api/v1/stats, aggregate counts only, no PII).

Deterministic equity-compensation tax math that any Model Context Protocol (MCP) client can call: incentive stock option (ISO) exercise schedules under the alternative minimum tax (AMT), non-qualified stock option (NSO) and restricted stock unit (RSU) decisions, qualified small business stock (QSBS) qualification, single-stock concentration, protective-put hedging, and equity-funding goals. Full federal tax code plus all 50 states and DC, 2026 brackets. Built by AlphaLatitude Inc., the company behind OptionsAhoy.

Why not just ask the model? We benchmarked five frontier large language models (LLMs), 3 runs each, 15 trials total, on the same multi-year ISO exercise problem. Every trial overshot the true after-tax outcome, by 2x to 20x. Multi-year scheduling has a search space larger than an LLM can reason through in-context; these tools return the verifiable answer instead. Live benchmark, updated for the latest models: optionsahoy.com/benchmark. Raw responses and scoring: llm-iso-benchmark. Full write-up: But can it do taxes though?

Install in one line

The hosted endpoint is https://optionsahoy.com/mcp (HTTP, no auth, no account). Quickest paths:

| Client | Install | |---|---| | Any MCP client | Add https://optionsahoy.com/mcp as a remote HTTP server, or npx add-mcp https://optionsahoy.com/mcp | | Claude Desktop | Download optionsahoy.mcpb and double-click it | | 19 clients via Smithery | npx @smithery/cli install alphalatitude/optionsahoy --client claude | | Local stdio (npm) | npx -y optionsahoy-mcp |

Full install matrix (Gemini CLI extension, config-file JSON, REST API, Google Cloud Agent Registry): optionsahoy.com/for-agents.

The seven tools

| Tool name | What it computes | |---|---| | amt_iso_optimize | Multi-year ISO exercise schedule that maximizes after-tax net final value at the planning horizon, modeling AMT credit recovery, grant expiration, and the post-termination exercise window | | nso_calculate | After-tax payout on an NSO exercise (federal, state, FICA), comparing sell-at-exercise vs hold for long-term capital gains | | rsu_sell_vs_hold | RSU vest decision: sell at vest vs hold for long-term capital gains, including the gap between 22% supplemental withholding and your marginal bracket | | concentration_analyze | Single-stock concentration risk (drawdown exposure at 30/50/70% downside), comparing after-tax sell-down, hold, and hedge strategies | | protective_put_price | Protective put and zero-cost collar pricing via Black-Scholes: annualized hedge cost, maximum loss, upside cap, floor-hit probability | | qsbs_check | Section 1202 QSBS qualification across the eight statutory tests, with the OBBBA 2026 tiered exclusion and per-state conformity | | equity_funding_plan | Multi-year, multi-stack sell schedule to hit a target after-tax amount by a deadline; returns four named plans plus the full risk/wealth frontier |

The optimizers return the best schedule across the candidate space; the calculators return exact deterministic results. Deterministic computation, not a language-model guess, validated against brute-force ground truth on tractable cases (see the proof). Coverage spans the full federal tax code (ordinary brackets, long-term capital gains, AMT with credit recovery, FICA, NIIT) plus all 50 states and DC (state ordinary brackets, LTCG treatment, state AMT for CA, CO, CT, MN). Same engine as the in-browser calculators at optionsahoy.com/tools; the API response is byte-identical to clicking through the tool.

Use it in your agent framework (Python)

If you build agents in Python rather than calling the MCP endpoint directly, OptionsAhoy ships installable tool packages for the major agent frameworks. Each one wraps the same calculators behind the framework's native tool interface. All are published on PyPI and all are keyless: no OptionsAhoy account, no API key.

| Framework | Install | Import | Example | |---|---|---|---| | LangChain | pip install optionsahoy-langchain | from langchain_optionsahoy import get_optionsahoy_tools | [equity_agent.py](integrations/python/optionsahoy-langchain/examples/equityagent.py) | | LlamaIndex | pip install llama-index-tools-optionsahoy | from llama_index.tools.optionsahoy import OptionsAhoyToolSpec | [equity_agent.py](integrations/python/llama-index-tools-optionsahoy/examples/equityagent.py) | | CrewAI | pip install crewai-optionsahoy | from crewai_optionsahoy import get_optionsahoy_tools | [equity_crew.py](integrations/python/crewai-optionsahoy/examples/equitycrew.py) | | Plain Python client | pip install optionsahoy | from optionsahoy import OptionsAhoyClient | [basic_client.py](integrations/python/optionsahoy/examples/basicclient.py) |

The three framework adapters pull in the keyless optionsahoy client automatically. There is also an [OpenBB Workspace agent](integrations/openbb-agent) (a FastAPI application built on the OptionsAhoy client) for use inside OpenBB Workspace. Source and runnable examples for all of the above live under integrations/python.

More ways to build

However your agent is built, there is a drop-in piece. All are public and keyless.

| Building block | What it is | |---|---| | [Instruction kits](integrations/agent-kits) | Editor rules and skills for Cursor, Windsurf, Claude Skills, and Claude Code subagents, so your coding agent calls the OptionsAhoy tools for equity-compensation questions. | | Coding recipes | Copy-paste Python recipes, one self-contained file per question, calling the keyless API with only requests. Also in [integrations/recipes](integrations/recipes). | | [Builder templates](integrations/agent-builder-templates) | An importable n8n workflow plus build recipes for Flowise, Langflow, and Dify. | | [Tool-use eval](integrations/eval) | An inspectai evaluation measuring whether an agent reaches the provable optimum on a multi-year ISO problem, with and without the tool. | | [A2A discovery](integrations/openbb-agent) | An Agent2Agent (A2A) Agent Card so other agents can discover and delegate equity-compensation questions to the planner. |

Try it without installing

The live widget on optionsahoy.com/for-agents calls this same endpoint from your browser. No client, no config.

Or watch a real session:

[](https://optionsahoy.com/for-agents#demo)

Real Claude Code session, unedited. A multi-stack META question (10K ISOs + 6K vested RSUs + 2K fresh RSUs + $400K house in 2027) fires 4 OptionsAhoy MCP tools in parallel: concentration risk, equity funding plan, AMT/ISO optimization, protective put pricing. Claude synthesizes the outputs into one plan that overrides each tool's standalone pick because the user is 86% concentrated in META. 2:13. Click the poster to play it on optionsahoy.com.

Endpoints and discovery

Live MCP endpoint: https://optionsahoy.com/mcp Live REST API: https://optionsahoy.com/api/v1 OpenAPI 3.1 spec: /openapi.json Discovery manifests: /.well-known/mcp.json · /.well-known/openapi.json Agent integration docs: optionsahoy.com/for-agents

MCP resources (topical briefings)

Six markdown resources under resources/list give an LLM enough grounding to discuss the topic before picking a tool. Each maps 1:1 with a cornerstone article on optionsahoy.com/learn and the matching calculator.

| Resource URI | Topic | Pair with | |---|---|---| | https://optionsahoy.com/learn/amt-crossover | ISO/AMT crossover and four expensive mistakes | amt_iso_optimize | | https://optionsahoy.com/learn/nso-sell-vs-hold | NSO sell-at-exercise vs hold-for-LTCG | nso_calculate | | https://optionsahoy.com/learn/rsu-withholding-gap | RSU 22% withholding gap and five April surprises | rsu_sell_vs_hold | | https://optionsahoy.com/learn/single-stock-concentration-risk | Concentration risk and diversification trade-off | concentration_analyze | | https://optionsahoy.com/learn/zero-cost-collars | Protective puts and zero-cost collars | protective_put_price | | https://optionsahoy.com/learn/qsbs | QSBS qualification and five ways to lose the exclusion | qsbs_check |

MCP prompts (workflow scaffolds)

Seven prompts under prompts/list scaffold typical user questions and route to the right tool. In Claude Desktop they appear as named slash-commands; in any MCP client, prompts/get { name, arguments } returns a fully-templated user message.

| Prompt name | Routes to | |---|---| | optimize-iso-exercise | amt_iso_optimize | | analyze-nso-decision | nso_calculate | | analyze-rsu-vest | rsu_sell_vs_hold | | analyze-concentration | concentration_analyze | | price-protective-put | protective_put_price | | check-qsbs-eligibility | qsbs_check | | plan-equity-funding | equity_funding_plan |

Install details

Claude Desktop extension (one-click)

The optionsahoy.mcpb bundle installs by double-click (or drag onto Claude Desktop → Settings → Extensions), with no terminal or config-file editing, using Claude Desktop's built-in Node.js runtime.

To build the bundle from source:

npm install && npm run build:mcpb

Smithery CLI (19 clients, one command)

npx @smithery/cli install alphalatitude/optionsahoy --client claude

Swap claude for any client Smithery supports: claude-code, cursor, vscode, gemini-cli, codex, windsurf, cline, goose, opencode, and 10 more. Listing: smithery.ai/servers/alphalatitude/optionsahoy.

Gemini CLI extension

gemini extensions install https://github.com/AlvisoOculus/optionsahoy-mcp

This repo doubles as a Gemini CLI extension: gemini-extension.json wires the hosted MCP endpoint and GEMINI.md provides usage context to the model.

Local stdio (npm)

For clients that only support local stdio servers (Claude Desktop without mcp-remote, some IDE integrations):

npx -y optionsahoy-mcp

Or add to a Claude Desktop / Cline / Goose config file:

{
  "mcpServers": {
    "optionsahoy": {
      "command": "npx",
      "args": ["-y", "optionsahoy-mcp"]
    }
  }
}

The local server returns byte-identical responses to the hosted endpoint at https://optionsahoy.com/mcp. Source for both lives in [functions/_lib/mcp-tools.ts](functions/_lib/mcp-tools.ts); the stdio entry point is [src/stdio-server.ts](src/stdio-server.ts).

Use the REST API directly

# List endpoints
curl https://optionsahoy.com/api/v1

# Run an optimization
curl -X POST https://optionsahoy.com/api/v1/amt-iso \
  -H "content-type: application/json" \
  -d @input.json

Request body shapes are documented in [public/openapi.json](public/openapi.json).

Repository layout

functions/         Cloudflare Pages Functions (MCP server + REST API endpoints)
  mcp.ts           HTTP MCP server
  api/v1/*.ts      Seven tool endpoints + stats + GET /api/v1 discovery
  _lib/*.ts        Shared helpers, calc-input parsers, MCP tool descriptors
lib/               Optimizer + tax-code logic
  calc/            Per-tool optimizer functions (computeAmtIso, etc.)
  tax/             Federal + 50-state + DC bracket data, AMT, FICA, NIIT
  markets/         Sector statistics
  options/         Black-Scholes, risk-free rates
  data/            Type definitions for option-chain data
public/            Static assets: OpenAPI spec, llms.txt, discovery manifests
tests/             Vitest suites (172 tests including byte-identity assertions)

Run tests

npm install
npm test         # 172 tests, ~3s on a laptop
npm run typecheck

Registry listings

• Official MCP Registry — io.github.AlvisoOculus/optionsahoy-mcp v1.0.0, status active
• Smithery — alphalatitude/optionsahoy (plus the equity-plan skill)
• Gemini CLI extensions gallery — @AlvisoOculus/optionsahoy-mcp
• add-mcp curated registry
• PulseMCP (cascades from Official Registry)
• Continue.dev hub — block YAML lives at [.continue/mcpServers/optionsahoy.yaml](.continue/mcpServers/optionsahoy.yaml)

Use from Google Cloud (Gemini agents)

Google Cloud Agent Registry lets each GCP project register external MCP servers for use by Gemini agents. Registration

…

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: AlvisoOculus
• Source: AlvisoOculus/optionsahoy-mcp
• License: MIT

Install and usage instructions live in the source repository linked above.