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ledger-mcp

ledger-mcp

by luke-nielsen
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

monthly_spending

View total monthly charges and expenses from your rent ledger. Optionally filter by year and category to identify discrepancies.

Instructions

Total spending (charges/expenses) per calendar month.

Optionally restrict to a year and/or category.

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": "monthly_spending"
  }
}

Input Schema

NameRequiredDescriptionDefault
yearNo
categoryNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

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 bears full responsibility for disclosing behavior, but it is minimal. It omits details on data range, ordering, default filters, whether accounts are aggregated, or output format, leaving significant gaps.

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 front-loaded sentences. It wastes no words, though it could benefit from slightly more detail without becoming verbose.

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's simplicity and presence of an output schema, the description is mostly adequate but omits default behavior when no filters are applied and does not clarify scope across accounts. It meets minimum viability.

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 description adds context that the parameters are for restriction, which the schema (with 0% property descriptions) lacks. However, it does not provide format specifics, valid values, or interaction semantics (e.g., AND vs OR).

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 provides total spending per calendar month, which is a specific aggregation. However, it does not explicitly differentiate from sibling tools like sum_transactions or transactions_by_category, leaving ambiguity.

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 only mentions optional restriction by year and category but provides no guidance on when to use this tool versus alternatives like check_late_fees or get_balance_sheet. No conditions or exclusions are stated.

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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