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PowerBI Analyst MCP

PowerBI Analyst MCP

by mbrummerstedt
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

delete_query_log_entry

Remove incorrect or misleading queries from the Power BI query history log while preserving associated CSV files for auditability.

Instructions

Remove a single entry from the query history log.

Use this when a query produced incorrect or misleading results and should not appear in future history searches. The associated CSV file (if any) is NOT deleted — only the log entry is removed.

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": {
      "entry_id": "<entry_id>"
    },
    "name": "delete_query_log_entry"
  }
}

Input Schema

NameRequiredDescriptionDefault
entry_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It excellently clarifies data preservation ('The associated CSV file...is NOT deleted'), which is critical for a deletion tool. Minor gap: it doesn't state whether the deletion is irreversible or mention any permission requirements.

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?

Three sentences with zero waste: purpose (sentence 1), usage context (sentence 2), and critical behavioral caveat (sentence 3). Information is front-loaded and density is high.

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?

Given the tool has an output schema (exempting return value documentation) and only one parameter, the description is nearly complete. It covers the primary behavioral quirk (CSV preservation). The only gap is the lack of parameter explanation necessitated by 0% schema coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% (entry_id lacks a description field), so the description must compensate. It fails to do so—never mentioning entry_id, its format, or how to obtain it (e.g., from search_query_history). 'Single entry' implies identification is needed but provides no semantics.

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 opens with the specific verb 'Remove' and identifies the exact resource ('single entry from the query history log'). It clearly distinguishes this from sibling tool search_query_history (which retrieves entries) and execute_dax (which creates entries).

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?

Provides explicit when-to-use guidance ('Use this when a query produced incorrect or misleading results'). It also clarifies the scope limitation ('should not appear in future history searches'), helping the agent understand this affects searchability rather than data storage.

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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