# Universal Document Vector Search Service

> Universal Document Vector Search Service — plvld-rag-service. Use this tool when you need to semantically search and retrieve documents, or navigate category hierarchies, to solve problems like information discovery and knowledge retrieval. It takes in search queries and document categories as inputs and outputs relevant documents and category hierarchies. Ideal for use cases where AI assistants require efficient document search and retrieval capabilities.

Canonical page: https://skillsregistry.net/skills/plvld-rag-service  
JSON: https://api.skillsregistry.net/v1/skills/plvld-rag-service

## Description

This MCP server provides semantic document search and retrieval, enabling AI assistants to search documents, search categories, and retrieve category hierarchies using the Model Context Protocol.

## Trust

- **Trust score (0–1):** 0.36
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/l617me3ac3)
- **Repository:** <https://github.com/PlVld/rag-service>

## 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": "plvld-rag-service"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/plvld-rag-service` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/plvld-rag-service/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