Data & AI

qdrant-search-quality - Claude MCP Skill

Diagnoses and improves Qdrant search relevance. Use when someone reports 'search results are bad', 'wrong results', 'low precision', 'low recall', 'irrelevant matches', 'missing expected results', or asks 'how to improve search quality?', 'which embedding model?', 'should I use hybrid search?', 'should I use reranking?'. Also use when search quality degrades after quantization, model change, or data growth.

SEO Guide: Enhance your AI agent with the qdrant-search-quality tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to diagnoses and improves qdrant search relevance. use when someone reports 'search results are bad', '... Download and configure this skill to unlock new capabilities for your AI workflow.

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Documentation

SKILL.md

# Qdrant Search Quality

First determine whether the problem is the embedding model, Qdrant configuration, or the query strategy. Most quality issues come from the model or data, not from Qdrant itself. If search quality is low, inspect how chunks are being passed to Qdrant before tuning any parameters. Splitting mid-sentence can drop quality 30-40%.

- Start by testing with exact search to isolate the problem [Search API](https://search.qdrant.tech/md/documentation/search/search/?s=search-api)


## Diagnosis and Tuning

Isolate the source of quality issues, tune HNSW parameters, and choose the right embedding model. [Diagnosis and Tuning](diagnosis/SKILL.md)


## Search Strategies

Hybrid search, reranking, relevance feedback, and exploration APIs for improving result quality. [Search Strategies](search-strategies/SKILL.md)

Signals

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Information

Repository: github/awesome-copilot
Author: github
Last Sync: 5/10/2026
Repo Updated: 5/10/2026
Created: 4/17/2026

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