Alternative Asset Literacy — Advisor

com.alternativeassetliteracy/aal-advisor-mcp · v1.0.1

Client-education toolkit for advisors: deep-dive tracks, calculators, free onboarding tools.

MCPremoteno credentialsFinanceResearch & education

Reported outcomes

No reports yet.

Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 32 tools, protocol 2025-03-26 · checked 2026-10-17

Test & rating

A 100/100

What it does: 32 tools · 32 read, 0 write · Finance, Law & government, Research & education

Test call glossary.browse: worked (1,029 ms)

How the rating is made

Answers without login: +30
Speed of first answer: +10
Lists tools: +10
Tool descriptions: +15
Parameter descriptions: +10
Read/write annotations: +5
Safe test call: +20
More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL

https://alternativeassetliteracy.com/mcp

Tools

32 tools listed at last check

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

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