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validate_mongo_query

Validate MongoDB find filters and aggregation pipelines without executing them, ensuring query correctness before running.

Instructions

Validate a find filter or aggregation pipeline without executing it.

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": {
      "connection_id": "<connection_id>",
      "collection": "<collection>",
      "operation": "<operation>"
    },
    "name": "validate_mongo_query"
  }
}

Input Schema

Name	Required	Description	Default
`filter`	No
`pipeline`	No
`operation`	Yes
`collection`	Yes
`connection_id`	Yes

Output Schema

Name	Required	Description
`valid`	Yes
`warnings`	Yes
`operation`	Yes	Operation family exposed through MCP and audit.
`collection`	Yes
`executable`	Yes
`blocked_reasons`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.9.0Aug 5, 2026

TDQS

A3.7/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the key non-execution behavior, but does not explain what validation entails (e.g., syntax checking, server-side parsing) or whether it requires an active connection. This is minimal but not misleading.

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?

A single sentence with no filler. It front-loads the verb and resource, and every word contributes meaning. Perfectly concise.

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

Completeness2/5

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

For a 5-parameter tool with sibling execution variants, the description is too sparse. It does not clarify which parameter combinations are valid (e.g., filter for find, pipeline for aggregate), how validation differs from execution, or what the output schema represents. The output schema exists but the description still needs to guide correct invocation, especially given the many similar Mongo tools.

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%, and the description offers no parameter-specific guidance. It only hints at 'filter' and 'pipeline' via the phrase 'find filter or aggregation pipeline', but does not explain the 'operation' enum, 'collection', or 'connection_id' requirements. The description fails to compensate for the lack of schema descriptions.

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 tool validates a find filter or aggregation pipeline without executing it. It uses a specific verb ('validate') and resource ('find filter or aggregation pipeline'), distinguishing it from sibling execution tools like execute_mongo_find and execute_mongo_aggregate.

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

Usage Guidelines4/5

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

The phrase 'without executing it' implies use as a pre-flight check before running a query, providing clear context. However, it does not explicitly name alternatives or state when not to use it, such as for SQL validation (validate_sql exists as a sibling).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.