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fynsight: MCP server for DATEV

generate-month-report

Create the first report draft of a run whose figures a person has already approved in the app (run status approved). Any other status is rejected with the status named; regenerating an existing report is not possible here (it can mark edited texts for review or drop them) and stays in the app. Fynsight's own AI writes the driver sentences of the headlines and the three summary sentences from the computed figures and the published explanations, so the figures and explanation texts of this period are sent to Fynsight's AI provider (see data flows in the documentation). The result is a DRAFT: it is reviewed, published and signed off in the app. If building the report fails, the run goes to failed (a new run and a new approval are then needed). Returns the deeplink to the report.

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": {
      "run_id": "<run_id>"
    },
    "name": "generate-month-report"
  }
}

Input Schema

NameRequiredDescriptionDefault
run_idYesUUID of the run (status approved)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations, the description discloses that figures and explanations are sent to an AI provider, that the output is a draft requiring human review and sign-off, that a build failure moves the run to failed requiring a new run and approval, and that the tool returns a deeplink.

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 front-loaded with the action and precondition, then efficiently layers rejection behavior, AI data flow, draft lifecycle, failure handling, and return value. It is somewhat long but each sentence contributes a distinct operational detail.

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

Completeness5/5

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

For a non-idempotent, non-destructive mutation tool with no output schema, the description covers the key prerequisites, data-sharing implications, output form, failure consequences, and return value. An agent has enough context to call it correctly or recognize when not to.

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 schema already documents the single run_id parameter at 100% coverage, including its approved-status requirement. The description reinforces the approved-status prerequisite but adds no new parameter-level meaning beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: creating the first report draft for an approved run. It clearly distinguishes this from siblings such as export-report and draft-report-comment by focusing on the initial draft generation step.

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

Usage Guidelines5/5

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

It explicitly states the prerequisite that the run must be approved and that any other status is rejected. It also states that regenerating an existing report is not possible here and must stay in the app, giving clear when-not guidance.

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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