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fynsight: MCP server for DATEV

export-report

Read-only

Generate a structured financial report as JSON. Supports P&L statement, KPI dashboard, and category breakdown report types.

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": {
      "report_type": "<report_type>"
    },
    "name": "export-report"
  }
}

Input Schema

NameRequiredDescriptionDefault
periodNoSingle period (YYYY-MM) for point-in-time reports
date_toNoEnd date for multi-period reports (YYYY-MM-DD or YYYY-MM)
date_fromNoStart date for multi-period reports (YYYY-MM-DD or YYYY-MM)
report_typeYesType of report to generate

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 safety is covered. The description usefully clarifies that output is JSON returned inline rather than a file export, despite the 'export' name, but adds nothing about size limits, whether results are persisted, or per-type return differences.

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?

Two tight sentences with the core action front-loaded and the supported variants immediately after. Every clause carries information; nothing is redundant padding.

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?

With no output schema, the description is the only place an agent can learn what the JSON actually contains, and it only says 'structured financial report' without per-type shape. Parameter and annotation coverage are strong, but the return-value gap leaves a real hole for a reporting tool.

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%, so the schema already documents period, date_from, date_to, and report_type. The description adds no extra meaning — it does not explain how period interacts with a date range or which parameters apply to which report type. 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?

States a specific verb and resource ("Generate a structured financial report as JSON") and enumerates the three supported report types, which an agent can map to the report_type enum. It does not distinguish itself from siblings such as generate-month-report, get_periodic_summaries, or query_kpis, which overlap heavily with the 'P&L / KPI dashboard' framing.

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?

Usage is only implied by the list of report types; there is no explicit statement of when to choose this over generate-month-report or compute_aggregates, nor any exclusion. An agent must infer selection criteria from the enum values alone.

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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