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mhajder

Ghostfolio MCP Server

by mhajder

Get Dividends

get_dividends
Read-onlyIdempotent

Retrieve dividend data grouped by day, week, month, quarter, or year to view payment amounts and yield.

Instructions

Get dividend data grouped by time period showing dividend payments and yield.

Retrieves dividend income data grouped by the specified time period, showing dividend payments, yield, and income patterns over time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
group_byNoGrouping period for dividend data. Options: day, week, month, quarter, yearmonth
date_rangeNoTime range for dividend data. Options: 1d, 1w, 1m, 3m, 6m, 1y, 2y, 5y, maxmax

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.5.0

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already convey read-only, idempotent, non-destructive behavior. The description adds that results are grouped by time period and emphasize payments, yield, and income patterns, but this mostly restates schema semantics rather than revealing deeper behavioral traits like pagination, currency handling, or data sources.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

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

The description is short but redundant: the second sentence largely paraphrases the first and adds only the vague phrase 'income patterns over time.' It is front-loaded, but not every sentence earns its place.

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 output schema and comprehensive parameter descriptions cover most invocation needs. However, the description lacks guidance for choosing between get_dividends and the closely named sibling get_dividends_for_import, which is a meaningful completeness gap given the sibling context.

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%, and both parameters have clear descriptions with defaults and allowed option lists. The description does not add meaningful details beyond the schema, so the baseline score of 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 clearly identifies the resource (dividend data), the grouping behavior, and the output dimensions (payments, yield). It is distinct enough from the sibling get_dividends_for_import, though it does not explicitly call out any sibling or differentiation.

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?

There is no guidance on when to use this tool versus alternatives such as get_dividends_for_import or other data retrieval tools. The description implies a reporting/analytics use case but never states exclusions or selection criteria.

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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