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MongoDB MCP Server

collection-schema

Read-only

Analyze MongoDB collection structure to identify field types, patterns, and document organization for data understanding and validation.

Instructions

Describe the schema for a collection

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
databaseYesDatabase name
collectionYesCollection name
sampleSizeNoNumber of documents to sample for schema inference
responseBytesLimitNoThe maximum number of bytes to return in the response. This value is capped by the server's configured maxBytesPerQuery and cannot be exceeded.
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows this is a safe read operation. The description adds no behavioral context beyond what annotations provide—it doesn't mention that this performs sampling for schema inference (implied by parameters), potential performance impacts, or typical response formats. However, it doesn't contradict annotations either.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place with no redundancy or fluff.

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?

Given that annotations cover safety (read-only, non-destructive) and schema covers all parameters, the description provides minimal but adequate context for a read operation. However, with no output schema and no explanation of what schema information is returned (e.g., field types, distributions), the description leaves gaps in understanding the tool's full utility, especially compared to siblings.

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 description coverage is 100%, so all parameters are documented in the schema. The description adds no parameter-specific information beyond what's in the schema—it doesn't explain how 'sampleSize' affects accuracy or what 'responseBytesLimit' means for practical use. With high schema coverage, baseline 3 is appropriate as the description doesn't enhance parameter understanding.

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?

The description clearly states the action ('Describe') and resource ('schema for a collection'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'collection-indexes' or 'collection-storage-size' that also provide collection metadata, leaving room for potential confusion about when to choose this specific tool.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'collection-indexes' for index information or 'collection-storage-size' for size metrics, nor does it specify prerequisites or typical use cases for schema analysis versus other collection operations.

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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