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zvec-mcp-server

zvec-mcp-server

Official
by zvec-ai
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Python
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optimize_collection

Idempotent

Optimize a vector collection to improve query performance and reduce storage by merging segments and rebuilding the index.

Instructions

Optimize the collection (e.g., merge segments, rebuild index).

This operation improves query performance and reduces storage overhead.

Args: params (OptimizeCollectionInput): Validated input parameters containing: - collection_name (str): Collection identifier

Returns: str: Success message or error message

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": {
      "params": "<params>"
    },
    "name": "optimize_collection"
  }
}

Input Schema

NameRequiredDescriptionDefault
paramsYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate idempotency and non-destructiveness. The description adds specific behavioral details (merge segments, rebuild index) and return type, but does not mention concurrency or locks.

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 concise, front-loaded with the core purpose, and organized with Args and Returns sections. No unnecessary information.

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

Completeness5/5

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

For a simple tool with one parameter and an output schema, the description covers the operation's effect, input, and return value sufficiently. No gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite context signals showing 0% schema description coverage, the tool description clearly documents the required parameter collection_name with its meaning. This compensates fully.

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 it optimizes collections (merge segments, rebuild index) to improve performance and reduce storage, distinguishing it from creation/deletion tools among siblings.

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?

The description implies optimization for better performance but lacks explicit guidance on when to use vs. alternatives or when not to use it. No comparison to sibling tools is provided.

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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