# MCP RAG Server

> Use this tool when you need to efficiently retrieve and generate content from a large corpus of documents, such as Markdown, text, PowerPoint, and PDF files, to solve problems like information overload and knowledge discovery. It indexes and searches documents using vector embeddings, supporting contextual chunk retrieval and incremental indexing. Ideal for applications requiring multilingual document management and retrieval-augmented generation.

Canonical page: https://skillsregistry.net/skills/karaage0703-mcp-rag-server  
JSON: https://api.skillsregistry.net/v1/skills/karaage0703-mcp-rag-server

## Description

Enables retrieval-augmented generation (RAG) by indexing and searching through documents (Markdown, text, PowerPoint, PDF) using vector embeddings with multilingual-e5-large model and PostgreSQL pgvector. Supports contextual chunk retrieval and incremental indexing for efficient document management.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-05-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/chqyzzf9kp)
- **Repository:** <https://github.com/karaage0703/mcp-rag-server>

## 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": "karaage0703-mcp-rag-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/karaage0703-mcp-rag-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/karaage0703-mcp-rag-server/pull`

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