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Better Qdrant MCP Server

Better Qdrant MCP Server

by wrediam
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

add_documents

Upload and process documents into a Qdrant collection using specified embedding services like OpenAI or Ollama. Define text chunk size and overlap for efficient semantic search integration.

Instructions

Add documents to a Qdrant collection with specified embedding service

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": {
      "filePath": "<filePath>",
      "collection": "<collection>",
      "embeddingService": "<embeddingService>"
    },
    "name": "add_documents"
  }
}

Input Schema

NameRequiredDescriptionDefault
chunkOverlapNoOverlap between chunks (optional)
chunkSizeNoSize of text chunks (optional)
collectionYesName of the collection to add documents to
embeddingServiceYesEmbedding service to use
filePathYesPath to the file to process

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the embedding service but doesn't cover critical aspects like whether this is a write operation (implied by 'Add'), potential side effects, error conditions, or performance characteristics. For a tool that likely modifies data, this is insufficient.

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 appropriately sized and front-loaded with the core action.

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?

Given the complexity of adding documents with embeddings (a write operation with processing steps), no annotations, and no output schema, the description is incomplete. It lacks details on behavior, output format, error handling, or integration context, leaving significant gaps for an AI agent.

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 the schema fully documents all parameters. The description adds no additional meaning beyond implying that documents are processed with embeddings, which is already suggested by the 'embeddingService' parameter. Baseline 3 is appropriate when the schema does the heavy lifting.

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 ('Add documents') and target resource ('to a Qdrant collection'), specifying the embedding service requirement. However, it doesn't differentiate from sibling tools like 'search' or 'delete_collection' beyond the basic verb.

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 like 'search' or 'list_collections', nor are prerequisites or typical use cases mentioned. The description only states what it does, not when it's appropriate.

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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