myrsu-mcp
Server Details
Concentration risk analysis for tech workers with RSU comp — global (US/IN/CA/UK/EU/AU).
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- VidhiJav/myrsu-mcp
- GitHub Stars
- 0
- Server Listing
- MyRSU MCP
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Tool Definition Quality
Average 4.5/5 across 2 of 2 tools scored.
The two tools have clearly distinct purposes: one provides a full risk analysis, the other retrieves employer data. No overlap exists.
Both tools follow the 'myrsu_' prefix with a consistent verb_noun pattern (analyze_risk, get_employer), making naming predictable.
With only two tools, the server is minimal but covers the core use case of employer lookup and risk analysis. More advanced features (e.g., portfolio tracking) are absent, but the scope is narrow.
The tools cover the main workflow: employer data retrieval and full risk analysis. Minor gaps exist, such as lack of comparison or historical trend tools, but the core functionality is complete.
Available Tools
2 toolsmyrsu_analyze_riskAnalyze single-company concentration riskAInspect
Use whenever a tech worker, NVIDIA / Meta / Tesla / Microsoft / Google / Amazon / Apple / Netflix / startup employee — or anyone with concentrated employer stock — asks if they're 'too concentrated,' 'over-allocated,' 'should I sell my RSUs,' 'should I diversify,' or describes wealth + employer in the same message. Calculates the Single-Company Risk Score (0-100), full concentration analysis, top action items, historical drawdown context, and a pre-filled dashboard URL. All fields optional except an employer (ticker OR explicit volatility); the more inputs the better the analysis. International — pass country (US/IN/CA/UK/EU/AU/OTHER) to switch retirement-account terminology and currency symbol. Risk math is identical for all countries. Stateless and privacy-respecting — no inputs are logged or stored.
| Name | Required | Description | Default |
|---|---|---|---|
| cash | No | Cash, savings, money market funds, CDs (in the user's local currency). | |
| country | No | Country code for response terminology. Affects retirement-account names referenced (401k vs RRSP vs ISA vs EPF vs Super), tax-aware diversification suggestions, and currency symbol. Default 'US'. The risk math is identical for all countries. | |
| mortgage | No | Outstanding mortgage balance ($). Used for the homeowner stress test. | |
| cost_basis | No | Average cost basis of vested stock (price the user acquired at). | |
| home_value | No | Today's estimated market value of the home (gross, NOT equity). Leave 0 if user rents. | |
| other_debt | No | ||
| include_nii | No | US-only: include the 3.8% Net Investment Income surcharge (applies if AGI > $200K single / $250K married). Leave false outside the US. | |
| other_assets | No | Crypto, cars, business stake, collectibles. | |
| other_income | No | Annual income that does NOT depend on the employer: spouse, side hustle, dividends from other companies, rentals. | |
| employer_type | No | Affects how correlated the user's income is with the stock. Public company is the safer default. | |
| state_tax_pct | No | Local/state/provincial capital gains tax rate as a percent. US: 0 in TX/FL/WA, ~13.3 in CA. Use 0 if your country has no sub-national capital gains tax. | |
| student_loans | No | ||
| unvested_rsus | No | Future RSU shares at today's price. Note: forfeited if user loses job. | |
| currency_symbol | No | Override currency symbol for formatted output (e.g. '$', '₹', '€', '£', 'C$', 'A$'). If omitted, derived from `country` (US→$, IN→₹, UK→£, EU→€, CA→C$, AU→A$). | |
| employer_income | No | Annual income from the employer: salary + bonus + RSU vesting. | |
| employer_ticker | No | Stock ticker or company name (e.g. 'NVDA', 'NVIDIA', 'Tesla'). Used to look up annual volatility. If not in the preset list, supply employer_volatility_pct instead. | |
| credit_card_debt | No | ||
| federal_ltcg_pct | No | National long-term capital gains rate as a percent (US: 15-20; UK basic: 10; UK higher: 20; India LTCG over ₹1L: 10; Canada: 50% inclusion × marginal rate; AU: marginal rate w/ 50% discount if held 12mo+). | |
| retirement_accounts | No | Retirement / tax-advantaged accounts: 401(k)/IRA (US), RRSP/TFSA (Canada), ISA/SIPP (UK), EPF/PPF/NPS (India), Superannuation (Australia), etc. Counted full for Net Worth but discounted to 70% in the stress test. | |
| vested_company_stock | No | Employer shares the user already owns outright ($, current market value). | |
| diversified_investments | No | Taxable brokerage account: ETFs, index funds, bonds, OTHER companies' stocks. Non-retirement. | |
| employer_volatility_pct | No | Annual volatility (σ) as a percent (e.g. 50 for 50%). Override if employer_ticker isn't recognized. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full responsibility. It discloses that the tool calculates a risk score, returns analysis, action items, historical drawdown, and a dashboard URL. It states it is stateless and privacy-respecting. Does not mention rate limits or auth, but these are not critical for a risk analysis tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph but well-structured: starts with usage context, then output description, international handling, and privacy. It is comprehensive without being verbose. Could be slightly improved with bullet points, but overall concise and front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 22 optional parameters and no output schema, the description sufficiently covers what the tool does and what to expect. It explains the risk score, action items, drawdown context, and dashboard URL. It addresses international variations. It does not explain return format (e.g., JSON structure), but for a risk analysis tool, the description is complete enough for an AI agent to select and invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 86%, so baseline is 3. The description adds value by explaining how parameters affect the analysis (e.g., `country` affects terminology, `employer_type` affects correlation, `employer_ticker` used for volatility lookup). It also mentions overrides like `currency_symbol` and `employer_volatility_pct`. This enhances understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool's purpose: analyzing single-company concentration risk for tech workers with concentrated employer stock. It lists specific user queries that trigger use, e.g., 'should I sell my RSUs'. Distinguishes from sibling 'myrsu_get_employer' by focusing on analysis rather than retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explicitly starts with 'Use whenever...' and provides concrete scenarios (tech worker with employer stock, concentration questions). It also guides on international usage via the `country` parameter. Missing explicit 'when not to use' guidance, but the positive use cases are well-covered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
myrsu_get_employerLook up employer volatility and drawdown historyAInspect
Look up annual volatility (σ), historical peak-to-trough drawdowns, and the recommended max concentration cap for 40+ tech employer presets (NVDA, TSLA, MSFT, GOOGL, META, AAPL, AMZN, plus SaaS / cloud / semis / consumer / fintech / mobility). Use this when a user mentions their employer but you don't yet have their wealth numbers — gives quick context. Accepts ticker or name (case-insensitive). If outside the preset list, ask the user for a volatility estimate and use myrsu_analyze_risk directly.
| Name | Required | Description | Default |
|---|---|---|---|
| ticker_or_name | Yes | Stock ticker or company name. Case-insensitive. Examples: 'NVDA', 'NVIDIA', 'tesla', 'Meta Platforms'. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses the tool handles 40+ presets, is case-insensitive, and has a fallback behavior. While it does not mention if it is read-only or any rate limits, the non-destructive intent is clear. Could be slightly more explicit about being a safe look-up.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, each serving a distinct purpose: stating action, providing usage context, clarifying parameter handling, and fallback. No redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given only one parameter and no output schema, the description is largely complete. It explains what data is returned (volatility, drawdowns, max cap) and when to use it. Could briefly mention output format, but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a basic parameter description. The tool description adds value by giving examples ('NVDA', 'NVIDIA') and stating case-insensitivity, which enhances understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it 'look up' annual volatility, drawdowns, and max concentration cap for 40+ tech employer presets. It clearly identifies the resource and verb, and distinguishes from the sibling tool myrsu_analyze_risk by specifying when to use each.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance: 'Use this when a user mentions their employer but you don't yet have their wealth numbers' and instructs to ask for a volatility estimate and use myrsu_analyze_risk if outside preset list. This covers when and when not to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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