# ollqd

> Use this tool when you need to efficiently search and index large codebases and documents, as it solves problems of information retrieval and discovery through semantic search capabilities. It takes in code and documents as input and outputs relevant search results, utilizing Ollama embeddings and Qdrant vector store. Ideal for use cases where quick and accurate code or document retrieval is crucial, such as in software development and knowledge management contexts.

Canonical page: https://skillsregistry.net/skills/leomarviegas-ollqd  
JSON: https://api.skillsregistry.net/v1/skills/leomarviegas-ollqd

## Description

Enables indexing and semantic search of codebases and documents via MCP, using Ollama embeddings and Qdrant vector store.

## Trust

- **Trust score (0–1):** 0.35
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/mi2gqtku6c)
- **Repository:** <https://github.com/leomarviegas/Ollqd>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "leomarviegas-ollqd"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/leomarviegas-ollqd` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/leomarviegas-ollqd/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt