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Finance Intelligence MCP

Finance Intelligence MCP

by Ronit-019
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

financial_health_score

Calculate your financial health score and receive feedback metrics to evaluate your financial status for any month.

Instructions

Calculate a deterministic financial health score and feedback metrics.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "financial_health_score"
  }
}

Input Schema

NameRequiredDescriptionDefault
reference_monthNoOptional target month to evaluate in YYYY-MM format. Defaults to current month.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It mentions 'deterministic' (implying reproducible results) but does not state whether the operation is read-only, what data it depends on, or any side effects or prerequisites. This is a notable gap for a financial 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. It communicates the core function efficiently, which is ideal given the tool's analytical nature.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the output schema may explain return values, the description omits crucial context such as data sources, prerequisites (e.g., requiring existing expense/budget data), and how the score is derived. For a tool with analytical complexity, this description falls short of being fully contextual.

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?

The sole parameter reference_month is fully described in the schema (optional, YYYY-MM format, defaults to current month), giving 100% schema coverage. The description adds no param information, so baseline 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 identifies the tool's action ('Calculate') and resource ('a deterministic financial health score and feedback metrics'), distinguishing it from simpler expense/budget list tools. However, it does not explicitly contrast with siblings like compare_budget_vs_expenses or expense_summary, so it earns a 4 rather than a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like expense_summary or compare_budget_vs_expenses. It only states what it calculates, leaving the agent to infer usage from the name and siblings.

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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