Skip to main content
Glama

MaCalculatriceEnLigne

Calculate Compound Interest Monthly

calculate_compound_interest_monthly
Read-onlyIdempotent

Compute compound interest with monthly contributions (savings plan). Use for systematic savers. Inputs: initial amount, monthly contribution, annual rate %, years. Returns final value, total contributed, total interest. See list_bundles for related 'finance-universal' calculators.

Input Schema

NameRequiredDescriptionDefault
yearsYesNumber of years
principalYesInitial capital EUR
annual_rateYesAnnual interest rate percent
monthly_contributionYesMonthly contribution EUR

Output Schema

NameRequiredDescriptionDefault
resultNoComputed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent and non-destructive behavior, so the safety profile is fully covered. The description adds the input list and a summary of return values, which is mild extra context, but it discloses nothing about edge cases (e.g., zero contributions, zero rate) or interpretation of the results.

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?

Purpose is front-loaded in the first sentence and the remaining sentences are short and information-bearing. The 'See list_bundles...' sentence is the weakest, adding a discovery pointer rather than helping invoke this specific tool.

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?

With an output schema present, the description needn't explain return format, and annotations cover safety, so the core call requirements are covered. Inputs and outcome are both mentioned; only edge-case behavior and sibling disambiguation are missing.

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 all four parameters are already documented in the schema, and the description's input list simply restates them. No additional meaning (units beyond 'EUR', sign conventions, or rate format) is supplied beyond what the schema already provides, so baseline 3 applies.

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 names a specific verb and resource ('Compute compound interest with monthly contributions') and scopes it with '(savings plan)', which distinguishes it from the plain compound-interest sibling. However, it never names calculate_compound_interest or calculate_future_value, so differentiation is implied rather than explicit.

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?

'Use for systematic savers' implies a usage context but gives no explicit when-not or alternative routing, even though close siblings like calculate_compound_interest and calculate_savings_goal exist. The list_bundles pointer is a discovery aid, not selection guidance for this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.