Alternative Asset Literacy — Retail

Alternative-asset education for retail investors: deep-dive tracks, calculators, advisor lookup.

Should I use this

Quality & Safety

B
Description quality
98%
Schema completeness
60%
Naming quality
48%
Poisoning risk
100%
Permission match
100%
Protocol compliance
100%

Findings (26)

  • LOWTool 'facts.random' description lacks action verbin facts.random
  • LOWTool 'glossary.lookup' doesn't follow camelCase/snake_casein glossary.lookup
  • LOWTool 'glossary.search' doesn't follow camelCase/snake_casein glossary.search
  • LOWTool 'glossary.browse' doesn't follow camelCase/snake_casein glossary.browse
  • LOWTool 'learn.list_modules' doesn't follow camelCase/snake_casein learn.list_modules
  • LOWTool 'learn.module' doesn't follow camelCase/snake_casein learn.module
  • LOWTool 'facts.random' doesn't follow camelCase/snake_casein facts.random
  • LOWTool 'toolkit.frameworks' doesn't follow camelCase/snake_casein toolkit.frameworks
  • LOWTool 'behavioral.brain_map' doesn't follow camelCase/snake_casein behavioral.brain_map
  • LOWTool 'art.learning_track' doesn't follow camelCase/snake_casein art.learning_track

Based on automated analysis of tool definitions and protocol compliance.

Context Cost

~3,950Tokens (tool definitions)
~879 BTypical response size
Significant attention impact (3.09% of 128k context)

This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.

Install

One-Click Install

Add this to your `claude_desktop_config.json` file:

{
  "mcpServers": {
    "aal-retail-mcp": {
      "url": "https://alternativeassetliteracy.com/mcp/retail"
    }
  }
}

Remote endpoints

https://alternativeassetliteracy.com/mcp/retailstreamable-http

What it can do

Tool inventory

Tools (22)

🟢 Read-only🟡 Write🔴 Delete⚪ Unknown
🟢glossary.lookup(term)

Look up a term from the app's 351-term glossary — always free in the app, always free here. Spans alternative assets, DeFi, ESG, behavioral economics, art, and gender lens investing.

Input Schema

{
  "type": "object",
  "properties": {
    "term": {
      "type": "string",
      "description": "The financial term to look up"
    }
  },
  "required": [
    "term"
  ]
}
🟢glossary.search(query, limit)

Full-text search across all 351 glossary terms and definitions.

Input Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "Keyword or phrase to search"
    },
    "limit": {
      "type": "number",
      "description": "Max results (default 10, max 50)"
    }
  },
  "required": [
    "query"
  ]
}
🟢glossary.browse(category, limit)

Browse all 351 glossary terms by category (Alternative Assets, Art, DeFi & Crypto, ESG & Climate, Behavioral Economics, Gender Lens Investing).

Input Schema

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "description": "Category to browse. Omit for all."
    },
    "limit": {
      "type": "number",
      "description": "Max terms (default 25, max 100)"
    }
  }
}
🟢learn.list_modules

Lists all 9 learning modules with a short description and whether each is free in full or preview-only — the same index as the app's own Learn tab.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "modules": {
      "type": "array"
    }
  },
  "required": [
    "modules"
  ]
}
🟢learn.module(module_id)

Returns the actual content (sections, quiz preview) for a learning module, gated exactly like the app: one module free in full, every other module capped at its first section(s)/quiz with the rest listed by title only and a link to subscribe for full access.

Input Schema

{
  "type": "object",
  "properties": {
    "module_id": {
      "type": "string",
      "description": "Module id or title (e.g. 'mod_art', 'Art as Investment') — see learn.list_modules for the full list"
    }
  },
  "required": [
    "module_id"
  ]
}
🟢facts.random(category)

A short, sourced statistic about women & finance, behavioral economics, alternative investing, or the art market.

Input Schema

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "enum": [
        "Women & Finance",
        "Behavioral Economics",
        "Alternative Investing",
        "Art Market"
      ],
      "description": "Optional category filter. Omit for any category."
    }
  }
}
🟢toolkit.frameworks

Full due-diligence/risk/tax checklists for an active plugin subscription (independent of the app's own subscription); otherwise titles and categories only, with a link to subscribe.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "items": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "items",
    "locked"
  ]
}
🟢behavioral.brain_map

Full content (hijack patterns, navigation strategies) for an active plugin subscription; otherwise the 4 region names and one-line functions only, with a link to subscribe.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "regions": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "regions",
    "locked"
  ]
}
🟢art.learning_track

Full lesson content (including 'Female Artists: An Overlooked Asset Class') for an active plugin subscription; otherwise the 3 track titles and lesson titles only, with a link to subscribe.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "tracks": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "tracks",
    "locked"
  ]
}
🟢art.library

Full summaries for an active plugin subscription; otherwise book/podcast/paper titles and authors only, with a link to subscribe.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "items": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "items",
    "locked"
  ]
}
🟢reading.list(category)

The app's curated reading list spanning behavioral economics, venture capital, economic history, and policy — always free in the app, always free here.

Input Schema

{
  "type": "object",
  "properties": {
    "category": {
      "type": "string",
      "description": "Optional category filter."
    }
  }
}

Output Schema

{
  "type": "object",
  "properties": {
    "items": {
      "type": "array"
    }
  },
  "required": [
    "items"
  ]
}
🟢disclosures.get

Returns the full regulatory disclosure, accredited investor definition, and risk disclosure that apply to this plugin's content — the same language used in the app itself. Call this any time a user asks about risk, eligibility, or what this content legally is/isn't.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "regulatory": {
      "type": "string"
    },
    "accredited_investor": {
      "type": "string"
    },
    "risk": {
      "type": "string"
    }
  },
  "required": [
    "regulatory",
    "accredited_investor",
    "risk"
  ]
}
🟢explain.holding(holding_type)

The complement to third-party MCP connectors that bridge your live brokerage accounts (Fidelity/Schwab/Vanguard-style) into Claude — those show WHAT you own; this explains what it IS. Given an asset type, returns the plain-language glossary term(s) always; for an active plugin subscription, also returns the specific cognitive bias most likely to distort how people think about this asset type and a due-diligence angle, otherwise a locked note.

Input Schema

{
  "type": "object",
  "properties": {
    "holding_type": {
      "type": "string",
      "description": "The asset type, e.g. 'private equity fund', 'DeFi position', 'art fund', 'ESG fund'"
    }
  },
  "required": [
    "holding_type"
  ]
}

Output Schema

{
  "type": "object",
  "properties": {
    "terms": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "terms",
    "locked"
  ]
}
🟢gender_lens.learning_track

A dedicated track on investing through a gender lens, treated as its own subject rather than a subcategory of ESG — the wealth gap in real numbers, the underfunding of women-led ventures as a genuine investment thesis, how the strategy works across public and private markets, the history behind the gap, and what the peer-reviewed research does and doesn't support. Full narrative content for an active plugin subscription; otherwise lesson titles and key takeaways only.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "title",
    "lessons",
    "locked"
  ]
}
🟢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 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). Worth knowing as part of doing your own homework on an investment thesis before acting on it. Full narrative content for an active plugin subscription; otherwise lesson titles and key takeaways only.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "title",
    "lessons",
    "locked"
  ]
}
🟢vc_pe.deep_dive_track

Why venture capital and private equity exist as their own category of investing, a full breakdown of what 'accredited investor' actually means and the real risk behind that gate (illiquidity, failure rates, manager dependency), and what a family office is — including the real 2026 cost and AUM-threshold numbers behind single-family vs. multi-family office structures. Full narrative content for an active plugin subscription; otherwise lesson titles and key takeaways only.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "title",
    "lessons",
    "locked"
  ]
}
🟢rwa.deep_dive_track

How traditional assets — Treasury bills, money-market funds, private credit, real estate — get represented as on-chain tokens, who actually holds the underlying asset, where '24/7 instant liquidity' claims hold up and where they don't, and what U.S. regulators have said about it as of early 2026. Grounded in SEC primary sources and live tokenized-asset market data. Full narrative content for an active plugin subscription; otherwise lesson titles and key takeaways only.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "title",
    "lessons",
    "locked"
  ]
}
🟢pe_secondaries.deep_dive_track

What a GP-led continuation fund actually is, the structural conflict of interest at its center seen from both the GP's and the LP's side, who has a stake in the outcome without a vote (portfolio-company employees, never accredited LPs themselves), the behavioral trap built into the 'roll or cash out' decision, and an honest look at whether longer hold periods serve patient capital or deferred accountability — including a carefully-hedged gender-lens hypothesis. Full narrative content for an active plugin subscription; otherwise lesson titles and key takeaways only.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "title": {
      "type": "string"
    },
    "lessons": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "title",
    "lessons",
    "locked"
  ]
}
🟢alts.illiquidity_pacing_stress_test(annual_commitment, vintage_years, fund_life_years, investment_period_years, rate_of_contribution, ...)

A real computation, not templated text: models what a multi-year program of private-fund commitments (PE, VC, private credit, etc.) actually does to your cash flow over its life — capital calls, distributions, unrealized value, and the single worst year for net cash flow — using a simplified, transparent adaptation of the Takahashi-Alexander pacing framework used in institutional private-markets planning. Runs against multiple named forward-looking growth scenarios by default, not just a historical-average assumption, so the result is a range, not one confident number. Pass annual_liquidity_budget to see exactly which years a stated liquidity budget would be breached. A free preview shows the peak liquidity need under one scenario; full multi-scenario comparison and year-by-year detail require a plugin subscription.

Input Schema

{
  "type": "object",
  "properties": {
    "annual_commitment": {
      "type": "number",
      "description": "Dollar amount you'd commit to new private-fund vintages each year"
    },
    "vintage_years": {
      "type": "number",
      "description": "How many consecutive years you keep making new commitments (default 5)"
    },
    "fund_life_years": {
      "type": "number",
      "description": "Assumed life of each fund vintage in years (default 12)"
    },
    "investment_period_years": {
      "type": "number",
      "description": "Years each vintage actively calls capital before calls stop (default 5)"
    },
    "rate_of_contribution": {
      "type": "number",
      "description": "Fraction of a vintage's uncalled capital called per year during its investment period (default 0.30)"
    },
    "rate_of_distribution": {
      "type": "number",
      "description": "Base annual distribution rate applied to unrealized value, back-loaded via a bow curve (default 0.20)"
    },
    "annual_liquidity_budget": {
      "type": "number",
      "description": "Optional — your actual annual liquidity budget for capital calls, to flag years it would be breached"
    },
    "scenario": {
      "type": "string",
      "description": "A single scenario id (historical_baseline, regime_transition, ai_productivity_acceleration, structural_stagnation) to run one scenario only — omit to see the full range (subscription required)"
    }
  },
  "required": [
    "annual_commitment"
  ]
}

Output Schema

{
  "type": "object",
  "properties": {
    "scenarios": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "scenarios"
  ]
}
🟢advisors.women_focused_directory

A discovery resource, not a recommendation — durable, self-updating advisor-search networks (NAPFA, XY Planning Network's Women's Finance filter, Garrett Planning Network, CFP Board) plus a short list of individually verified fee-only firms with a genuine, publicly-stated focus on women clients or gender-lens investing, each with the specific public statement it's grounded in. Built on real demand data: McKinsey/Cerulli research on women as a large, fast-growing, and demonstrably underserved segment of financial-advice demand. Free preview shows the durable networks and firm names; full verification details and public-statement citations require a plugin subscription.

Input Schema

{
  "type": "object",
  "properties": {}
}

Output Schema

{
  "type": "object",
  "properties": {
    "durable_networks": {
      "type": "array"
    },
    "firms": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "durable_networks",
    "firms"
  ]
}
🟢retirement.monte_carlo_estimator(current_age, retirement_age, life_expectancy, current_savings, annual_contribution, ...)

A real Monte Carlo simulation — thousands of trials, not one deterministic projection — estimating the odds your savings and contributions support your 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; you state your own target income and the tool reports the odds under each named forward-looking scenario. Runs across multiple market-assumptions.js scenarios by default (historical baseline, regime transition, AI-productivity acceleration, structural stagnation) so you see how sensitive your plan actually is to an assumption most calculators bake in silently. Pair with alts.illiquidity_pacing_stress_test to see how an alternative-asset allocation affects overall retirement success odds. Free preview shows the success rate under one scenario; full multi-scenario comparison and percentile detail require a plugin subscription.

Input Schema

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

Output Schema

{
  "type": "object",
  "properties": {
    "scenarios": {
      "type": "array"
    },
    "locked": {
      "type": "boolean"
    }
  },
  "required": [
    "scenarios"
  ]
}
🟢advisors.registration_check(query, search_type)

Free, live lookup against the public, unauthenticated SEC Investment Adviser Public Disclosure (IAPD) and FINRA BrokerCheck registries — no subscription required for this tool. 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 your own due diligence, never a substitute for reading the full public record.

Input Schema

{
  "type": "object",
  "properties": {
    "query": {
      "type": "string",
      "description": "The advisor or firm name to search for"
    },
    "search_type": {
      "type": "string",
      "enum": [
        "individual",
        "firm"
      ],
      "description": "Whether to search for a person or a firm"
    }
  },
  "required": [
    "query",
    "search_type"
  ]
}

Output Schema

{
  "type": "object",
  "properties": {
    "results": {
      "type": "array"
    }
  },
  "required": [
    "results"
  ]
}

Community

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Evidence

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