# mcpRAG

> Use this tool when you need to answer frequently asked questions about Formula 1, as it provides relevant information through vector search and web search using Bright Data, accepting user queries as input and returning accurate answers as output, ideal for contexts where up-to-date and reliable F1 information is required. It solves problems of outdated or incorrect information by leveraging web search capabilities. This tool is particularly useful for users seeking quick and accurate answers to common F1 questions.

Canonical page: https://skillsregistry.net/skills/patanjali-22-rag-app-mcp  
JSON: https://api.skillsregistry.net/v1/skills/patanjali-22-rag-app-mcp

## Description

Enables answering Formula 1 FAQ questions via vector search and web search using Bright Data.

## Trust

- **Trust score (0–1):** 0.69
- **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/wb16w65678)
- **Repository:** <https://github.com/patanjali-22/RAG-App-MCP>

## 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": "patanjali-22-rag-app-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/patanjali-22-rag-app-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/patanjali-22-rag-app-mcp/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