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fynsight: MCP server for DATEV

query_kpis

Read-only

Calculate KPI values for a given period. Returns each KPI with value, previous-period value, and month-over-month change. Use for KPI-specific questions.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "period": "<period>"
    },
    "name": "query_kpis"
  }
}

Input Schema

NameRequiredDescriptionDefault
periodYesAccounting period in YYYY-MM format (e.g. '2025-03')
kpi_idsNoOptional list of KPI IDs to filter. Omit for all active KPIs.
include_previousNoInclude previous-period comparison (default true)

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 readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds useful output context (each KPI returned with current, previous-period, and MoM change), but says nothing about how results change when include_previous is false or what happens for KPIs with no prior-period data.

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?

Three short sentences, front-loaded with the action followed by the return shape and then the usage cue. Little waste, though the final sentence is thin filler relative to what could have been a real disambiguation note.

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?

Read-only, three fully documented flat parameters, and the return fields are described in prose despite no output schema. What is missing for full completeness is the boundary against sibling trend/aggregate tools.

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%, including the YYYY-MM period format, the optional kpi_ids filter, and the include_previous default, so the schema carries the parameter burden. The description's mention of previous-period comparison loosely reinforces include_previous but adds no semantics beyond the schema.

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?

States a specific verb and resource ('Calculate KPI values for a given period') and previews the return shape (value, previous-period value, month-over-month change). It does not name or distinguish itself from the closest siblings (get_metric_trend, compute_aggregates), so an agent must infer the boundary from the 'KPI-specific' phrasing.

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 KPI-specific questions' gives a positive trigger but no exclusions, prerequisites, or guidance versus get_metric_trend or get_periodic_summaries. The reader is left to infer when a KPI query is the wrong choice.

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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