# Content Server

> Use this tool when you need to manage and store organizational content in a centralized location, solving problems of data dispersion and inaccessible information. It accepts various types of content as input and provides secure storage and retrieval capabilities as output. Ideal for use cases where centralized content management is crucial, such as document management, knowledge bases, and digital asset management.

Canonical page: https://skillsregistry.net/skills/yogeshkulkarni553-rag-mcp-py  
JSON: https://api.skillsregistry.net/v1/skills/yogeshkulkarni553-rag-mcp-py

## Description

Stores Organizations content

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/imldyz4189)
- **Repository:** <https://github.com/yogeshkulkarni553/rag-mcp-py>

## 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": "yogeshkulkarni553-rag-mcp-py"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/yogeshkulkarni553-rag-mcp-py` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/yogeshkulkarni553-rag-mcp-py/pull`

---
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