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avaazquezz

io.github.avaazquezz/mcp-qdrant

by avaazquezz

qdrant_points_count

Read-onlyIdempotent

Count points in a Qdrant collection, with optional filters to match specific criteria. Get the total number of vectors or a filtered subset count.

Instructions

Count points in a collection, optionally matching a filter.

    Example: {"collection_name": "docs"}
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
exactNo
count_filterNo
collection_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYesNumber of points which satisfy the conditions

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.1.1

TDQS

B3.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint true, idempotentHint true, and destructiveHint false, covering the safety profile. The description adds that the filter is optional and gives a minimal example, but it does not disclose behavior around the 'exact' parameter, performance cost, or what happens when the collection does not exist.

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 one compact sentence plus a minimal example, with no filler or redundant explanation. The action and resource are front-loaded, and every element earns its place.

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 read-only point-counting tool with a complex filter schema and an output schema, the description is minimally adequate. It captures the core operation and filter optionality, but it omits the meaning of 'exact' and any collection-existence or performance caveats, so it is not fully complete.

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%, so the description must compensate, but it only notes that a filter is optional and shows a collection_name example. The non-obvious 'exact' boolean parameter is left completely unexplained, which is a significant gap for correct invocation.

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 a specific action and resource: 'Count points in a collection, optionally matching a filter.' This distinguishes it from retrieval siblings such as points_get, points_scroll, and query, though it never names an alternative, so it stops short of a 5.

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?

No guidance is given about when to use this tool versus alternatives like qdrant_points_scroll, qdrant_query, or qdrant_collection_info. 'Optionally matching a filter' implies a use case, but there are no explicit conditions, exclusions, or alternative routing.

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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