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qdrant-llamaindex-mcp-server

qdrant-llamaindex-mcp-server

by azhang
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

qdrant-get-collection-count

Retrieve the total point count in a specified collection to monitor its size or validate data loading.

Instructions

Get the number of points in a collection.

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": {
      "collection_name": "<collection_name>"
    },
    "name": "qdrant-get-collection-count"
  }
}

Input Schema

NameRequiredDescriptionDefault
collection_nameYesThe name of the collection to count

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral traits. It only states the basic operation without noting any side effects, authentication needs, or limitations (e.g., counting only points, not all stored data). This is insufficient for an agent to assess the tool's behavior.

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, concise sentence with no extraneous words. It efficiently conveys the core purpose.

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 simple tool with no output schema, the description should specify the return format. It states 'Get the number of points' but does not indicate whether the result is an integer, a JSON object, or something else. This missing detail reduces completeness.

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% (the single parameter has a description). The tool description adds no additional meaning beyond the schema, so baseline score of 3 applies.

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's purpose with a specific verb ('get') and resource ('number of points'), distinguishing it from sibling tools like get-collection-details which retrieve more comprehensive information.

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 provided on when to use this tool versus alternatives. There is no mention of performance implications, prerequisites, or context for using the count operation.

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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