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drill-mcp

drill-mcp

Official
by apache
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

cancel_query

Cancel a running Apache Drill query by its query ID to halt execution immediately and free cluster resources.

Instructions

Cancel a running query by its query id.

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": {
      "query_id": "<query_id>"
    },
    "name": "cancel_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
query_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It only states the action without explaining side effects, whether cancellation is immediate or asynchronous, what happens if the query ID is invalid, or if there are any prerequisites. This is a significant gap for a mutation tool.

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?

The description is a single, front-loaded sentence with no redundant information. Every word earns its place, making it highly concise and scannable.

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?

For a simple one-parameter tool, the description is minimally adequate, but it lacks caveats like idempotency, error behavior, or asynchronous completion. While an output schema exists, the description still leaves important operational details to guesswork.

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?

The schema provides a bare 'query_id' string with no description (0% coverage). The description only repeats 'by its query id' without clarifying formats, where to find it, or any constraints. This does not compensate for the lack of schema documentation.

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 clearly states the action ('Cancel') and the resource ('a running query'), with the identifier method ('by its query id'). This distinctively separates it from siblings like run_query, making the purpose unambiguous.

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 context is implied by the description and name; the agent can infer it should be used when a query is running and needs to be stopped. However, there is no explicit guidance on when to use it versus alternatives or when not to use it, such as if the query has already completed.

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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