wealth-engine

by Jaume9

Overview Schema Related Servers Score Discussions

TypeScript

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct personal finance task: budgeting, growth projection, debt payoff, FIRE, freelancing, loans, pricing, investment comparison, side hustles, subscriptions, and taxes. Descriptions clearly differentiate them, and no two tools have overlapping purposes.
Naming Consistency4/5
All tool names follow snake_case and a predominantly noun_verb pattern (e.g., compound_growth, debt_payoff). The minor exception is budget_analyzer (noun_verb) instead of budget_analyze, but the pattern is still clear and consistent overall.
Tool Count5/5
With 11 tools, the count feels perfectly scoped for a personal finance assistant. Each tool covers a distinct aspect without overwhelming the user or agent, making the set manageable and focused.
Completeness4/5
The toolset covers budgeting, investing, debt, loans, taxes, and FIRE comprehensively. Minor gaps exist, such as no general retirement planning beyond FIRE or expense tracking, but the core workflows are well-covered.
Average 4/5 across 11 of 11 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It mentions fitting a linear demand curve, deriving optimal price from unit economics, and returning a transparent price sweep. However, it does not disclose computational assumptions, limitations (e.g., linearity), or potential side effects. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences long, front-loaded with the main purpose, and contains no extraneous information. Every sentence adds value, making it concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description mentions 'returns a transparent price sweep' and reports both profit- and revenue-maximizing prices. However, it lacks explicit details on the output format or structure, which would improve completeness. Mostly sufficient but with a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% as all parameter descriptions are provided in the schema. The description adds context like 'observed price/quantity points' and 'unit economics', but does not significantly extend beyond the schema's own descriptions. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds the price that maximizes profit, fitting a linear demand curve. It specifies the resource (product/service) and verb (find/optimize). However, it could be more specific about the return format to fully distinguish from similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for profit maximization and revenue maximization, but does not explicitly state when NOT to use the tool or provide comparisons to sibling tools like 'freelance_rate' or 'roi_compare'. Guidelines are implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It explains that each opportunity is a cash flow series and that period 0 is typically negative. However, it does not disclose edge cases, error handling, or the exact output format (only says 'tells you which option creates the most value').
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no fluff. It front-loads the core purpose and immediately follows with essential context about cash flows.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema and no annotations, the description is somewhat incomplete. It does not specify the return format (e.g., a sorted list or comparison table), which would help an agent understand how to use the result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters adequately. The description adds context about ROI, NPV, etc., but that relates more to purpose than parameter details. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The title and description clearly state the tool compares multiple investments on ROI, NPV, IRR, and payback period. The verb 'compare' and resource 'investments' are specific, and the tool is distinct from siblings that focus on single analyses (e.g., compound_growth).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for comparing multiple cash flow streams to find the best value, but it does not explicitly state when not to use it or provide alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description sets expectations by mentioning it computes estimates based on inputs and assumed return/withdrawal rates. It discloses after-tax income and inflation-adjusted return, adding behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences, front-loaded with the main purpose. It efficiently conveys required inputs and outputs, though it could be slightly more telegraphic.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters, no output schema, and no annotations, the description adequately explains what it does and key outputs. It misses some delimitations (constant spending, no inflation variable), but is complete enough for a calculator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add new parameter details beyond what the schema provides, but listing outputs (FIRE number, savings rate, years) aids understanding of parameter roles. No significant added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the tool computes FIRE number, savings rate, and years to FI using income, expenses, investments, and return. It uses specific verbs and distinguishes from sibling tools like compound_growth and budget_analyzer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates use for retirement planning, but lacks explicit when-to-use, when-not-to-use, or alternative tools. Given sibling names, the context is somewhat clear but could be more directive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions accounting for non-billable time, vacation, taxes, and expenses, but does not disclose default values or output format. Adequate but not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the core purpose, and appends a useful warning. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema is provided, and the description does not specify the return value (presumably hourly rate) or any additional info like defaults. Given 6 parameters and no output description, completeness is adequate but missing key details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good descriptions in the schema itself. The description adds marginal value by referencing concepts like target income and non-billable time, but does not significantly enhance parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates hourly rate for freelancers to achieve target income, accounting for non-billable time, vacation, taxes, and expenses. It distinguishes itself from siblings which cover budgeting, growth, debt, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: for freelancers/consultants transitioning from salary, and warns against using salary/2080. It does not explicitly state when not to use or name alternatives, but context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description carries full burden. It explains the analysis performed but does not disclose side effects, auth needs, or that the tool is read-only. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence front-loads the purpose and lists key actions without waste. Every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately conveys the return value (quantified savings) and the overall process. Could benefit from mentioning output format or prerequisites, but sufficient for an analysis tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. The description adds value by explaining how parameters are used in computations (annualization, cost-per-use, low-value flags), providing meaningful context beyond field names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Audit' and resource 'recurring subscriptions', detailing actions: annualize, compute cost-per-use, flag low-value, quantify savings. It clearly distinguishes from sibling tools like budget_analyzer or debt_payoff.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for auditing subscriptions to find savings, but does not explicitly state when to use this over alternatives or give exclusions. Lacks comparative guidance,
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It transparently describes the tool as an analyzer that surfaces overspending and recommendations, implying read-only, non-destructive behavior. However, it does not explicitly state that no modifications occur or mention any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no redundancy. The first sentence identifies the purpose and rule, the second lists actionable outputs. Perfectly front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given two parameters and no output schema, the description fully covers input requirements and expected results (overspending, unallocated money, split comparison, recommendations). No gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds overall context (50/30/20 rule) but does not enhance understanding of individual parameters beyond the schema, which already describes them clearly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it analyzes a monthly budget against the 50/30/20 rule, listing specific outputs like overspending and recommendations. This distinguishes it from sibling financial calculators such as debt_payoff or fire_calculator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly indicates use for budget analysis but provides no explicit guidance on when to use this tool vs alternatives like side_hustle_ranker or subscription_audit. No when-not-to-use or context hints are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It lists key factors accounted for (startup cost, ramp time, etc.), which sets expectations. However, it omits output details (e.g., whether it returns a ranked list or scores) and does not mention any limitations or safety considerations, leaving some transparency gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no wasted words. The structure clearly states what the tool does and the value it provides.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains input factors well but lacks information about the output format (ranked list vs. scores) and any constraints (e.g., maximum number of hustles). Given no output schema, this omission reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds little new per-parameter information beyond what is already in the schema. It provides context on how parameters are combined into the risk-adjusted value, but does not elaborate on parameter usage beyond the schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it ranks side-hustle ideas by risk-adjusted effective hourly value, considering specific factors like startup cost, ramp time, etc. It distinguishes itself from sibling financial tools by focusing on side-hustle comparison, using a concrete verb and resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly frames the tool as a numbers-driven decision maker for 'which side hustle should I start?', clearly indicating its use case. However, it does not provide exclusions or mention when to use alternatives like budget_analyzer or freelance_rate, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, but description discloses outputs and optional features. For a stateless calculator, this is sufficient; no contradictions or missing critical behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first defines action and output, second provides usage context. No fluff, front-loaded, every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lists return values and mentions inflation adjustment and schedule, but no output schema. For a financial calculator, this is fairly complete; a bit more detail on the schedule format could improve, but not required for clarity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds minimal per-parameter detail beyond schema, tying parameters to overall calculation but not enriching individual parameter meanings.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Explicitly states it projects investment growth with compounding and contributions, lists return values (future value, total contributed, interest earned, real value, schedule), and provides a clear use-case question.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Clear context: 'how much will my investing turn into?'. Does not explicitly mention when not to use or suggest alternatives among sibling tools, but the usage context is well-defined.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It explains the simulation behavior, including rolling freed-up payments and reporting months to debt-free and total interest. However, it does not disclose any underlying assumptions or limitations, such as interest rate constancy.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, concise and well-structured. It front-loads the core action and includes key details without unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description mentions expected results (months to debt-free, total interest, winning strategy). It covers the main behavior and output, though it could mention edge cases or prerequisites (e.g., ensuring monthlyBudget >= sum of minimum payments).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all parameters. The tool description adds context about avalanche vs. snowball methods and rolling payments, enhancing understanding beyond the schema. It does not add new parameter details but reinforces their use.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: planning debt payoff using avalanche and/or snowball methods, simulating month-by-month, and reporting results. The title and content distinguish it from sibling tools like budget_analyzer and loan_amortization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus siblings. It only describes what it does, leaving the agent to infer usage context from the tool's name and category.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It discloses default behavior (US 2024 single-filer) and customizability, plus outputs (total tax, after-tax income, breakdown, rates). It does not mention side effects or requirements, but as a calculator, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three well-structured sentences with no redundancy. Purpose is front-loaded, and every sentence adds essential information. Highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculator with 3 parameters and no output schema, the description explains inputs (including defaults and custom brackets) and outputs (total tax, breakdown, rates). It is complete and self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value by explaining default bracket usage and customizability, and it notes the deduction parameter (though not by name). It provides context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it estimates income tax under a progressive bracket schedule, specifying default US brackets and customizability. It is distinct from sibling financial tools like budget_analyzer or loan_amortization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for tax estimation but does not explicitly state when to use versus alternatives or provide exclusions. It lacks explicit guidance on when to choose this tool over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description transparently explains the tool's function (build schedule, accept extra payments, report interest savings and payoff date). Missing details on side effects or read-only nature, but these are implicitly understood for a calculation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler, front-loaded with main purpose. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex tool with 5 parameters and no output schema, the description adequately explains purpose and key outputs. However, it could mention the return format to complete the picture.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value beyond schema by mentioning 'recurring extra principal payments' and 'reports the interest those extra payments save plus the new payoff date', which contextualizes the extraPayment parameter and output behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool builds a full amortization schedule for loans, specifies support for extra principal payments and reporting of savings, and distinguishes from siblings by mentioning fixed-rate installment loans.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states use cases (mortgages, auto loans, fixed-rate loans), but lacks explicit when-not-to-use or alternative suggestions, which would further clarify against sibling tools like debt_payoff.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![wealth-engine-mcp MCP server](https://glama.ai/mcp/servers/Jaume9/wealth-engine-mcp/badges/card.svg)](https://glama.ai/mcp/servers/Jaume9/wealth-engine-mcp)

Score Badge

Copy to your README.md:

[![wealth-engine-mcp MCP server](https://glama.ai/mcp/servers/Jaume9/wealth-engine-mcp/badges/score.svg)](https://glama.ai/mcp/servers/Jaume9/wealth-engine-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Jaume9/wealth-engine-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server