# Alternative Asset Literacy — Advisor (remote · alternativeassetliteracy.com)

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

- Trust score: 67/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-09-29

## Components

- remote · `alternativeassetliteracy.com`: 67/100 (this document), [markdown](https://verifymcp.io/servers/com-alternativeassetliteracy-aal-advisor-mcp/alternativeassetliteracy.md), [page](https://verifymcp.io/servers/com-alternativeassetliteracy-aal-advisor-mcp/alternativeassetliteracy)

## Channel facts

- Endpoint: `https://alternativeassetliteracy.com/mcp`
- Transports: `streamable-http`
- Auth: `none`
- Version: `1.0.1`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-09-29.

- **Endpoint Security**: 63/100
  - The endpoint's TLS certificate is valid, in date, and uses a strong key.
  - No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one.
  - HTTPS check failed: the endpoint is reachable over plaintext HTTP.
  - HSTS check failed: the Strict-Transport-Security header is absent.
  - DNSSEC check failed: this domain isn't protected by DNSSEC.
- **Transport & Reachability**: 100/100
  - Verified streamable-http transport via a live MCP handshake.
- **Schema Quality & AI Usability**: 74/100
  - AI-judged instruction clarity (excellent).
  - Context-footprint check failed: tool/resource definitions use about 4535 tokens (~141/item across 32 items; 32 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 17/100
  - Stability observed for 5 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 32 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 32 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 40/100
  - Spec-recency check failed: implements MCP spec 2025-03-26; the latest is 2026-07-28.

## Install

### How do I install the Alternative Asset Literacy — Advisor MCP server?

Alternative Asset Literacy — Advisor is a hosted endpoint at https://alternativeassetliteracy.com/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add --transport http com-alternativeassetliteracy-aal-advisor-mcp 'https://alternativeassetliteracy.com/mcp'
```

### Cursor

```json
{
  "mcpServers": {
    "com-alternativeassetliteracy-aal-advisor-mcp": {
      "url": "https://alternativeassetliteracy.com/mcp"
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "com-alternativeassetliteracy-aal-advisor-mcp": {
      "type": "http",
      "url": "https://alternativeassetliteracy.com/mcp"
    }
  }
}
```

### Codex

```toml
[mcp_servers.com-alternativeassetliteracy-aal-advisor-mcp]
url = "https://alternativeassetliteracy.com/mcp"
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "com-alternativeassetliteracy-aal-advisor-mcp": {
      "type": "remote",
      "url": "https://alternativeassetliteracy.com/mcp",
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add com-alternativeassetliteracy-aal-advisor-mcp --url 'https://alternativeassetliteracy.com/mcp' --transport streamable-http
```

### Hermes

```yaml
mcp_servers:
  com-alternativeassetliteracy-aal-advisor-mcp:
    url: "https://alternativeassetliteracy.com/mcp"
```

### Netclaw

```json
{
  "McpServers": {
    "com-alternativeassetliteracy-aal-advisor-mcp": {
      "Transport": "http",
      "Url": "https://alternativeassetliteracy.com/mcp"
    }
  }
}
```

### Vellum

```bash
assistant mcp add com-alternativeassetliteracy-aal-advisor-mcp -t streamable-http -u 'https://alternativeassetliteracy.com/mcp'
```

### Other

```json
{
  "mcpServers": {
    "com-alternativeassetliteracy-aal-advisor-mcp": {
      "type": "http",
      "url": "https://alternativeassetliteracy.com/mcp"
    }
  }
}
```

The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-09-29 (score 67, +1)

No change was recorded against any check on this day. Stability & Change Management went from 13 to 17. That category is still filling its 30-day observation window: 4 days of observed history at the previous scan, 5 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-09-28 (score 66, 0)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-09-27 (score 66, +1)

- [security] Tool “advisor.registration_check” rewrote its description, which is the text the model reads

### 2026-09-25 (score 65, +1)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-09-24 (score 64)

First indexed and scored.

## MCP tools (32)

### `glossary.lookup` (~72 tokens)

Look Up Financial Term

Look up a financial term from the 351-term glossary spanning alternative assets, DeFi, ESG, behavioral economics, art, and gender lens investing.

Input parameters:

- `term` (string, required): The financial term to look up (e.g. 'carried interest', 'impermanent loss', 'TCFD', 'green bonds')

Output parameters:

- `category` (string): Glossary category (e.g. Alternative Assets, DeFi & Crypto, Art, ESG & Climate)
- `definition` (string): Full educational definition of the term
- `source` (string): Attribution and source URL
- `term` (string): The matched financial term

### `glossary.search` (~92 tokens)

Search Financial Glossary

Full-text search across all 351 financial terms and definitions — alternative assets, DeFi, behavioral economics, art, ESG, and gender lens investing.

Input parameters:

- `limit` (number): Max results to return (default 10, max 50)
- `query` (string, required): Keyword or phrase to search across term names and definitions (e.g. 'carbon credit', 'liquidity pool', 'loss aversion')

Output parameters:

- `glossary_url` (string): URL to full glossary
- `query` (string): The search query
- `terms` (array): Matching terms sorted by relevance
- `total_matches` (integer): Total number of matching terms found

### `glossary.browse` (~116 tokens)

Browse Glossary by Category

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.

Input parameters:

- `category` (string): Category to browse — e.g. 'Art', 'DeFi & Crypto', 'ESG & Climate', 'Behavioral Economics', 'Alternative Assets', 'Gender Lens Investing'. Omit for all categories.
- `limit` (number): Max terms to return (default 25, max 100)

Output parameters:

- `categories_available` (array): All available glossary categories
- `category_requested` (string): The category filter applied
- `glossary_url` (string): URL to full glossary
- `terms` (array): Terms in the requested category
- `terms_in_category` (integer): Number of terms matching the category
- `total_terms` (integer): Total terms in the glossary

### `research.papers` (~99 tokens)

Get Institutional 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.

Input parameters:

- `category` (string): Category: CBDC, Stablecoin, ESG, Behavioral Economics, Gender Lens, Fintech, Cross-Border Payments. Omit for all categories.

Output parameters:

- `all_categories` (object): Present instead of 'papers' when no category filter is given
- `category` (string)
- `papers` (array)

### `advisor.daily_prep` (~95 tokens)

Prep for a Day of Client Meetings

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 was mentioned. No calendar access — the advisor supplies the meeting list directly.

Input parameters:

- `meetings` (array, required): The day's meetings

Output parameters:

- `meeting_count` (integer)
- `meetings` (array)

### `advisor.gift_bundle` (~207 tokens)

Build Advisor Client 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 advisor → client gifting workflow. Works for HNW women, DeFi-curious clients, ESG-focused clients, art collectors, and general alternative asset education.

Input parameters:

- `client_description` (string, required): Description of the client — their background, wealth level, interests, upcoming meeting context, or knowledge gaps (e.g. 'HNW woman who just sold her biotech company, meeting with UBS next month', 'D…
- `topic` (string): Optional topic focus — overrides profile matching if provided (e.g. 'DeFi', 'ESG', 'art investing', 'alternative assets')

Output parameters:

- `client_profile_matched` (string): The investor profile matched to this client description
- `free_entry` (object): The free module and how to access it — no account required
- `further_research` (string): Pointer to other plugin tools for deeper material — never an external product
- `gift_type` (string)
- `learning_path` (array): 3-module curated path with 'why this matters' for each module
- `suggested_advisor_message` (string): Copy-paste message the advisor can send to the client
- `terms_to_know_before_next_meeting` (array): 3 key glossary terms the client should understand before their meeting
- `toolkit_highlights` (array): Relevant Toolkit features for this client

### `modules.get_content` (~167 tokens)

Get Module Content Preview

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 Kahlo x Basquiat bonus module. Mirrors the app's own free-tier preview exactly: the Investing Primer module returns in full, every other module returns its first section(s) and first quiz in full with the remainder listed by title only. This is narrative educational content only, not priced intelligence data.

Input parameters:

- `module_id` (string, required): Module id or title (e.g. 'mod_art', 'Art as Investment', 'mod_defi_investing', 'DeFi Investing')

Output parameters:

- `access_tier` (string): 'full_free_module' or 'free_preview'
- `id` (string)
- `quizzes` (array)
- `sections` (array)
- `title` (string)

### `facts.random` (~96 tokens)

Get a Random Investing Fact

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.). Educational teaser content, not the priced AAL intelligence data.

Input parameters:

- `category` (string): Optional category filter. Omit for any category.

Output parameters:

- `category` (string)
- `fact` (string)
- `source` (string)

### `advisor.meeting_icebreaker` (~126 tokens)

Get a Meeting Icebreaker Kit

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-term glossary), so there is never a 'subscribe to unlock' seam in the output — it's a complete, finished deliverable every time, not a locked preview.

Input parameters:

- `topic` (string): Optional topic to bias the opener toward. Omit for a surprise pick.

Output parameters:

- `fact` (object): The sourced statistic used
- `term` (object): The related glossary term used

### `advisor.risk_conversation_guide` (~182 tokens)

Get a 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 is always returned, each flagged with whether its general risk level aligns with what the client stated, so a mismatch is always a visible, explicit result rather than a silently omitted option. Also returns cross-cutting behavioral risk factors that apply regardless of category. This is educational risk categorization, not a recommendation or suitability determination.

Input parameters:

- `client_risk_tolerance` (string, required): The client's stated risk tolerance, in their own words or yours (e.g. 'conservative', 'moderate', 'aggressive, comfortable with volatility', 'capital preservation focused')

Output parameters:

- `areas` (array): All investment areas, each with risk_level, key_risk_factors, liquidity_profile, further_research, and aligns_with_stated_tolerance
- `band` (string): Classified tolerance band: conservative, moderate, aggressive, or unspecified
- `behavioral` (object): Cross-cutting behavioral risk factors that apply to every category

### `toolkit.frameworks` (~119 tokens)

Get a Due Diligence / Risk / Tax Framework

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 Diligence', 'Professionals', 'Risk Management', 'Tax & Legal') or by asset class (e.g. 'Art', 'DeFi', 'Private Equity').

Input parameters:

- `category` (string): Optional category or asset-class filter. Omit for all 12 frameworks.

Output parameters:

- `items` (array)

### `behavioral.brain_map` (~106 tokens)

Get the Investing 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 naming it.

Input parameters:

- `region` (string): Optional region name/id filter (e.g. 'amygdala', 'prefrontal'). Omit for all 4.

Output parameters:

- `regions` (array)

### `art.learning_track` (~113 tokens)

Get the Art Investor 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 diligence, working with professionals). Distinct from the main Art as Investment module.

Input parameters:

- `track` (string): Optional track id/title filter (e.g. 'female-artists-track'). Omit for all 3 tracks.

Output parameters:

- `tracks` (array)

### `art.library` (~104 tokens)

Search the 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.

Input parameters:

- `category` (string): Optional category filter. Omit for all.
- `query` (string): Optional free-text search across title/author/summary

Output parameters:

- `results` (array)
- `total` (integer)

### `reading.list` (~52 tokens)

Get the Curated 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.

Input parameters:

- `category` (string): Optional category filter.

Output parameters:

- `items` (array)

### `advisor.competency_check` (~182 tokens)

Get an 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, signs of a competent answer, and why it matters — written from the client's side, but directly usable by an advisor prepping for exactly the questions a sophisticated client might ask. Use it to self-check fluency before a meeting, or to anticipate pushback on a specific topic.

Input parameters:

- `topic` (string): Optional topic filter: 'defi', 'esg', 'alt', 'art', 'behavioral', 'gender', or 'general' — or a free-text match against the set/category titles. Omit for all 7 sets.

Output parameters:

- `sets` (array)

### `disclosures.get` (~132 tokens)

Get Legal Disclosures

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 message the advisor actually sends a client (gift_bundle's suggested_advisor_message, post_meeting_followup's client_followup_message, or a compliance_scan-flagged draft) — never send 'regulatory' to a client, since it names this plugin's own company and a client has no relationship with it.

Output parameters:

- `accredited_investor` (string)
- `client_facing` (string)
- `regulatory` (string)
- `risk` (string)

### `advisor.explain_holding` (~174 tokens)

Explain a Client's 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 client perceives this asset class (from the investing brain map), a matching due-diligence framework reference, and one non-suitability-asserting talking point for the meeting.

Input parameters:

- `client_risk_tolerance` (string): Optional, for context only — this tool does not make a suitability determination
- `holding_type` (string, required): The asset type or structure, e.g. 'private equity fund', 'DeFi position', 'hedge fund', 'art fund', 'ESG fund'

Output parameters:

- `behavioral_note` (object)
- `due_diligence_reference` (object)
- `plain_language_terms` (array)
- `suggested_talking_point` (string)

### `advisor.post_meeting_followup` (~177 tokens)

Generate a Post-Meeting Education Follow-Up

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 suggests, and how to navigate it — never sent to the client), a separate ready-to-send client follow-up message with a term, a sourced fact, and a suggested next module, and a pre-send compliance self-check run automatically against that message (same pattern scan as advisor.compliance_scan) so a flag surfaces before you have to think to ask for one.

Input parameters:

- `client_description` (string): Optional client context
- `topics_discussed` (string, required): Free-text description of what came up in the meeting, in the advisor's own words

Output parameters:

- `advisor_coaching_note` (object)
- `client_followup_message` (string)
- `compliance_self_check` (object)
- `suggested_next_module` (object)

### `advisor.compliance_scan` (~136 tokens)

Scan a Draft Client Communication

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, and missing accredited-investor/risk disclosure when the draft discusses PE, VC, hedge funds, DeFi, or art funds. Returns flagged passages with severity and a concrete suggested fix — for the missing-disclosure case, pointing to disclosures.get for the exact language to insert.

Input parameters:

- `draft_text` (string, required): The advisor's draft client communication to check

Output parameters:

- `clean` (boolean)
- `flags` (array)

### `advisor.commitment_pacing_model` (~453 tokens)

Illiquidity Stress-Test / 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, transparent adaptation of the Takahashi-Alexander pacing framework. Every rate (contribution pace, distribution pace, fund life) is a visible input, not a black box. Runs against multiple named forward-looking growth scenarios by default (not just a historical-average assumption) so the result is shown as a range, not one confident number — set scenario to a single id to see just one. Pass annual_liquidity_budget to flag exactly which years a stated liquidity budget would be breached. This is the practice-level version of alts.illiquidity_pacing_stress_test in the retail plugin — same engine, framed for a client conversation and due-diligence file note rather than the investor's own planning.

Input parameters:

- `annual_commitment` (number, required): Dollar amount committed to new private-fund vintages each year
- `annual_liquidity_budget` (number): Optional — the client's actual annual liquidity budget for capital calls, to flag years it would be breached
- `fund_life_years` (number): Assumed life of each fund vintage in years (default 12)
- `investment_period_years` (number): Years each vintage actively calls capital before calls stop (default 5)
- `rate_of_contribution` (number): Fraction of a vintage's uncalled capital called per year during its investment period (default 0.30)
- `rate_of_distribution` (number): Base annual distribution rate applied to NAV, back-loaded via a bow curve (default 0.20)
- `scenario` (string): A single market-assumptions.js scenario id (historical_baseline, regime_transition, ai_productivity_acceleration, structural_stagnation) to run one scenario only — omit to run the default set and see…
- `vintage_years` (number): How many consecutive years the client keeps making new commitments (default 5)

Output parameters:

- `scenarios` (array)

### `advisor.retirement_monte_carlo_estimator` (~374 tokens)

Retirement Cash-Flow 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 output of one specific historical regime, not a law; the client (or you, on their behalf) states the target income, and the tool reports the odds under each named forward-looking scenario. Runs across multiple market-assumptions.js scenarios by default so you can show a client how sensitive their plan actually is to an assumption most off-the-shelf calculators bake in silently. Pair with advisor.commitment_pacing_model to show how an alternative-asset allocation affects overall retirement success odds. This is an educational planning-conversation aid, not a substitute for your firm's own planning software or a specific recommendation.

Input parameters:

- `annual_contribution` (number, required): Amount contributed per year, in today's (real) dollars, during the years between current_age and retirement_age
- `current_age` (number, required): The client's current age in years
- `current_savings` (number, required): Current portfolio balance in today's (real) dollars
- `desired_annual_retirement_income` (number, required): The client's own target annual retirement income in today's (real) dollars — required; this tool will not assume a withdrawal rate
- `equity_weight` (number): Fraction of the portfolio in equity-like assets, 0-1 (default 0.6)
- `life_expectancy` (number): Planning horizon age (default 90)
- `retirement_age` (number, required): The age the client plans to retire and begin withdrawals
- `scenario` (string): A single scenario id to run one scenario only — omit to run the default set and see the range

Output parameters:

- `scenarios` (array)

### `advisor.registration_check` (~158 tokens)

Check a Firm or Individual's Public Registration

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/inactive, broker-dealer and/or investment-adviser) and whether the public record has any disclosure event on file, merged from both sources since each surfaces a different half of the disclosure picture. Always a starting point for due diligence, never a substitute for reading the full public record.

Input parameters:

- `query` (string, required): The advisor or firm name to search for
- `search_type` (string, required): Whether to search for a person or a firm

Output parameters:

- `results` (array)

### `defi.deep_dive_track` (~74 tokens)

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 commentary.

Output parameters:

- `lessons` (array)
- `title` (string)

### `esg.deep_dive_track` (~95 tokens)

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 greenwashing detection, and a balanced, two-sided account of what the peer-reviewed literature does and doesn't yet settle.

Output parameters:

- `lessons` (array)
- `title` (string)

### `art.deep_dive_track` (~107 tokens)

Art Market 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 historical context, not current conditions — the two studies also reach genuinely different conclusions from each other. Distinct from art.learning_track (art history/appreciation).

Output parameters:

- `lessons` (array)
- `title` (string)

### `behavioral.deep_dive_track` (~91 tokens)

Behavioral Economics 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 producing new findings. Distinct from behavioral.brain_map (neuroscience of 4 brain regions).

Output parameters:

- `lessons` (array)
- `title` (string)

### `gender_lens.advisor_practice_track` (~125 tokens)

Gender Lens Investing — Advisor Practice Guide

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, and peer-reviewed research for having the conversation credibly. Distinct from advisor.competency_check's gender-lens questions (client-side pushback) and from the retail plugin's gender-lens track (investor education) — this is specifically about what an advisor does differently in their own practice.

Output parameters:

- `lessons` (array)
- `title` (string)

### `gdr.deep_dive_track` (~158 tokens)

Gross Domestic Regeneration (GDR) — An Emerging Economic Model

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 framework, grounded against decades of real, verified 'beyond GDP' precedent (Bhutan's Gross National Happiness Index, the UN's SEEA Ecosystem Accounting standard, state-level Genuine Progress Indicators, Doughnut Economics) so the advisor can distinguish the well-established whole-systems critique from GDR's own current, unvalidated status. Relevant due-diligence context when a client raises whole-systems or beyond-GDP investment theses.

Output parameters:

- `lessons` (array)
- `title` (string)

### `vc_pe.deep_dive_track` (~116 tokens)

Venture Capital & Private Equity — Access, Verification, and the Family Office Question

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 Family Office Rule and real 2026 SFO/MFO cost and AUM-threshold data. Written from the advisor's own practice/compliance perspective, distinct from the retail plugin's investor-facing version of this same subject.

Output parameters:

- `lessons` (array)
- `title` (string)

### `pe_secondaries.deep_dive_track` (~122 tokens)

PE/VC Secondaries & Continuation Funds — What the Advisor of Record Needs to Ask

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 client and the GP, and how to frame the triple-bottom-line and gender-lens angles honestly, as hypotheses, rather than as advocacy. Written from the advisor's own practice/compliance perspective, distinct from the retail plugin's investor-facing version of this same subject.

Output parameters:

- `lessons` (array)
- `title` (string)

### `rwa.deep_dive_track` (~115 tokens)

Tokenized Real-World Assets — What the Advisor of Record Actually Needs to Know

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 the liquidity mismatch rather than the technology, and where SEC regulatory guidance actually stands as of January 2026. Written from the advisor's own practice/compliance perspective, distinct from the retail plugin's investor-facing version of this same subject.

Output parameters:

- `lessons` (array)
- `title` (string)

## Diagnostics

Captured diagnostic sections: TLS, DNSSEC, Authorisation, Transports. The full working is on the page: https://verifymcp.io/servers/com-alternativeassetliteracy-aal-advisor-mcp/alternativeassetliteracy#diagnostics

## Score history

- 2026-09-29: 67
- 2026-09-28: 66
- 2026-09-27: 66
- 2026-09-26: 65
- 2026-09-25: 65
- 2026-09-24: 64

## Common questions

### What is the Alternative Asset Literacy — Advisor MCP server?

Alternative Asset Literacy — Advisor is an MCP server listed in the public MCP registry as com.alternativeassetliteracy/aal-advisor-mcp. Client-education toolkit for advisors: deep-dive tracks, calculators, free onboarding tools. This page covers its hosted endpoint (https://alternativeassetliteracy.com/mcp).

### Is the Alternative Asset Literacy — Advisor MCP server safe to use?

Alternative Asset Literacy — Advisor scores 67 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the Alternative Asset Literacy — Advisor MCP server expose?

Alternative Asset Literacy — Advisor exposes 32 tools: glossary.lookup, glossary.search, glossary.browse, research.papers, advisor.daily_prep, and 27 more. Their descriptions and schemas cost roughly 4,535 tokens of context every time the server is loaded.

### Does the Alternative Asset Literacy — Advisor MCP server require authentication?

No. We connected to Alternative Asset Literacy — Advisor without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.

### Is the Alternative Asset Literacy — Advisor MCP server still maintained?

Alternative Asset Literacy — Advisor is still listed as active in the MCP registry. We last reached this channel on 29 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

## Links

- Remote endpoint: https://alternativeassetliteracy.com/mcp
- Repository: https://github.com/untitledfinancial/aal-plugins
- Changelog RSS feed: https://verifymcp.io/servers/com-alternativeassetliteracy-aal-advisor-mcp/alternativeassetliteracy.xml
- Changelog JSON feed: https://verifymcp.io/servers/com-alternativeassetliteracy-aal-advisor-mcp/alternativeassetliteracy.json
- HTML version of this page: https://verifymcp.io/servers/com-alternativeassetliteracy-aal-advisor-mcp/alternativeassetliteracy