com.alternativeassetliteracy/aal-advisor-mcp · v1.0.1 · finance-and-payments
Alternative Asset Literacy — Advisor is healthy: it completed an MCP handshake in 1053 ms and exposes 32 tools.
Client-education toolkit for advisors: deep-dive tracks, calculators, free onboarding tools.
Endpoint: https://alternativeassetliteracy.com/mcp (streamable-http)
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| Users (last 30 days) | 0 |
| Handshake | Healthy |
| Auth needed | None |
| Tool count | 32 |
| Latency | 1053 ms |
| Last checked (UTC) | 2026-10-17T01:55:38.369Z |
| Checked (UTC) | Status | Latency | Error |
|---|---|---|---|
| 2026-10-17T01:55:38.369Z | Healthy | 1053 | |
| 2026-10-15T19:05:11.898Z | Healthy | 1402 | |
| 2026-10-14T18:00:46.523Z | Healthy | 1257 | |
| 2026-10-14T18:00:46.481Z | Healthy | 1476 |
glossary.lookup | Look up a financial term from the 351-term glossary spanning alternative assets, DeFi, ESG, behavioral economics, art, and gender lens investing. |
glossary.search | Full-text search across all 351 financial terms and definitions — alternative assets, DeFi, behavioral economics, art, ESG, and gender lens investing. |
glossary.browse | Browse all 351 glossary terms by category. Categories: Alternative Assets, Art, DeFi & Crypto, ESG & Climate, Behavioral Economics, Gender Lens Investing. Omit category to browse all terms. |
research.papers | Returns institutional research papers by category — 43 papers from IMF, BIS, World Bank, FSB, UN, Federal Reserve, EU, IFC, OECD, and TCFD. The 'further research' destination other tools point to instead of an external product. |
advisor.daily_prep | Batch version of client meeting prep: given a list of the day's meetings (client description + optional topic + optional time each), returns a compact prep briefing for every meeting in one call — matched topic, 2 key terms, one sourced opener fact, and a risk-alignment snapshot if a risk tolerance |
advisor.gift_bundle | For financial advisors: given a description of a client, returns a curated education bundle the advisor can share — a 3-module learning path, 3 key terms the client should know before their next meeting, a copy-paste suggested message to send the client, and toolkit highlights. Designed for the advi |
modules.get_content | Returns the actual educational content (sections, citations, quiz preview) for one of the app's 9 live learning modules — Investing Primer, Alternative Investing, Behavioral Economics, Gender and Behavioral Investing, DeFi, Art as Investment, Climate/ESG & Real World Assets, DeFi Investing, and the |
facts.random | Returns a short, sourced statistic about women & finance, behavioral economics, alternative investing, or the art market — e.g. for a daily fact, loading screen, or conversation starter. Each fact is attributed to its original source (McKinsey, Bloomberg, Preqin, academic research, etc.). Educationa |
advisor.meeting_icebreaker | The free flagship onboarding tool: a ready-to-use meeting opener combining one sourced statistic with one related glossary term and a suggested opening line — for an advisor to use in the first 60 seconds of a client call. Draws only from unconditionally free content (the fact bank and the full 351- |
advisor.risk_conversation_guide | Maps a client's stated risk tolerance against the general risk characteristics of each alternative asset category (DeFi, private equity/VC, art & collectibles, ESG/climate, alternative investing/real estate) — for use alongside, never in place of, the advisor's own suitability review. Every category |
toolkit.frameworks | Returns asset-class-spanning advisor frameworks — due diligence checklists, red flags, risk assessment, position sizing, tax considerations, essential legal documents, advisor-team building, total-cost breakdowns, and market research databases. Optionally filter by category ('Research', 'Due Diligen |
behavioral.brain_map | Returns the neuroscience of investment decision-making — the prefrontal cortex, amygdala, nucleus accumbens, and anterior insula — each with its investing relevance, how it gets 'hijacked' into bad decisions, and concrete navigation strategies. Useful for explaining WHY a bias happens, not just nami |
art.learning_track | Returns the app's standalone Art Learning Track — 3 tracks, 9 lessons total: Art Concepts & Practices (value, market fundamentals, evaluation), Female Artists: An Overlooked Asset Class (the historical valuation gap and market opportunity), and The Art Investor's Toolkit (research resources, due dil |
art.library | Searches the app's curated art library — books, podcasts, and academic papers on art history, markets, and investing — sourced live from the same Notion databases the app itself reads. Filter by category ('books', 'podcasts', 'papers') and/or a free-text query against title, author, and summary. |
reading.list | Returns the app's curated reading list spanning behavioral economics, venture capital, economic history, and policy — each with author, year, summary, and an Apple Books link. |
advisor.competency_check | Returns the app's 'Questions for Your Financial Advisor' question sets — 53 questions across 7 categories (DeFi/crypto, ESG/climate, alternative investing, art, behavioral finance, gender-lens investing, and general fiduciary/planning basics). Each question includes signs of an inadequate answer, si |
disclosures.get | Returns two distinct kinds of disclosure, plus the accredited investor definition and risk disclosure. 'regulatory' is for the advisor's own reading/records — what this plugin's content legally is/isn't. 'client_facing' is separate, deliberately un-branded boilerplate meant to be appended to any mes |
advisor.explain_holding | Complements data connectors that surface a client's actual holdings (e.g. iCapital's NAV/commitments, Addepar's portfolio data) but never explain what the holding IS. Given an asset type or structure label, returns a plain-language definition, the specific cognitive bias most likely to distort how a |
advisor.post_meeting_followup | Complements meeting-intelligence tools (e.g. Zocks, Wealthbox) that capture WHAT was discussed but don't generate client-facing educational content. Given a description of the topics discussed, returns three things: a private coaching note for the advisor (which cognitive bias the client's language |
advisor.compliance_scan | Complements Anthropic's general AI-policy compliance skill with a narrower check scoped specifically to alternative-asset client communications, using the same suitability-neutral and anti-anecdotal rules this plugin enforces on its own output: anecdotal/FOMO framing, suitability-assertion language, |
advisor.commitment_pacing_model | A real computation, not templated text: models what a multi-year program of private-fund commitments (PE, VC, private credit, etc.) actually does to a client's cash flow over its life — capital calls, distributions, unrealized NAV, and the single worst year for net cash flow — using a simplified, tr |
advisor.retirement_monte_carlo_estimator | A real Monte Carlo simulation — thousands of trials, not one deterministic projection — estimating the odds a client's savings and contributions support their stated retirement income target. Deliberately does NOT assume a fixed withdrawal rule like the '4% rule,' since that figure is itself an outp |
advisor.registration_check | Live lookup against the public SEC Investment Adviser Public Disclosure (IAPD) and FINRA BrokerCheck registries — no seat required. Useful for centers-of-influence due diligence — a referral partner, a co-sourcing firm, a peer practice — not just for clients. Returns registration scope (active/inact |
defi.deep_dive_track | A rigorous look at decentralized finance as an asset class — protocol-level revenue mechanics (Aave, Uniswap), real failure modes (Terra/Luna, smart contract exploits), sizing/custody/tax discipline, and an honest account of how thin the peer-reviewed DeFi literature still is relative to industry co |
esg.deep_dive_track | ESG investing evaluated on the Triple Bottom Line it's actually built on (People, Planet, Profit — Elkington, 1994), not financial return alone — why ratings diverge across providers, real fee/cost/performance data (including a genuinely improving financial-return trend since 2019), systematic green |
art.deep_dive_track | The financial and legal mechanics of the art market — advisor conflicts of interest, provenance/authentication risk, primary-vs-secondary market signals, current market data (2023-2025 Artprice100 index performance), and older academic return studies (Mei & Moses; Renneboog & Spaenjers) presented as |
behavioral.deep_dive_track | The decision-making layer underneath every asset class — advisor self-awareness (not just client bias), structural tools that manage client behavior better than reassurance, framing effects, mental accounting, and the peer-reviewed foundations (Kahneman & Tversky, De Bondt & Thaler) that are still p |
gender_lens.advisor_practice_track | The advice gap and gender-lens investing gap treated as practice risks an advisor actively manages — auditing your own recommendation patterns, couples/continuity dynamics most practices haven't built a process for, facilitating a client's gender-lens request with real screening and due diligence, a |
gdr.deep_dive_track | A recently proposed (2026), NOT institutionally adopted alternative to GDP — measuring an economy by what it regenerates (ecological, social, and capital dimensions, treated as interdependent) rather than what it produces. Explicitly caveated throughout as an unvalidated, single-thought-leader frame |
vc_pe.deep_dive_track | Why VC and PE exist as their own asset classes, what verifying a client's accredited investor status actually requires of the advisor of record (506(b) self-certification vs. 506(c) mandatory verification), and how to recognize and navigate the family-office conversation — including the SEC's 2011 F |
pe_secondaries.deep_dive_track | How to evaluate a client's roll-or-cash-out decision in a GP-led continuation fund — the specific governance questions (fairness opinion provenance, LPAC engagement) that separate a well-run transaction from a rubber stamp, the fee-clock incentive and behavioral-framing dynamics pulling on both the |
rwa.deep_dive_track | How to talk about tokenized Treasuries, money-market funds, and other on-chain-wrapped assets with a client without conflating them with speculative crypto — the due-diligence questions that actually matter (structural model, redemption cap, custodian concentration), suitability framing centered on |