# rag-paper

> Use this tool when you need to efficiently search and manage academic PDFs, or when you want to enrich metadata and visualize citation graphs for research purposes. It provides a local-first solution with a user-friendly interface, accepting PDF files and metadata as inputs and outputting searchable and organized academic papers. Ideal for researchers and academics seeking to streamline their literature review and organization process.

Canonical page: https://skillsregistry.net/skills/i1ight-ragpaper  
JSON: https://api.skillsregistry.net/v1/skills/i1ight-ragpaper

## Description

A local-first paper RAG server that enables searching and managing academic PDFs via MCP tools, supporting metadata enrichment and citation graphs.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/xf4lrqu246)
- **Repository:** <https://github.com/i1ight/ragPaper>

## 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": "i1ight-ragpaper"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/i1ight-ragpaper` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/i1ight-ragpaper/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