# faq-rag

> Use this tool when you need to generate human-like answers to frequent questions from existing FAQ documents. It solves the problem of providing accurate and relevant responses to user inquiries by leveraging vector search and large language model (LLM) generation. The tool takes in natural-language questions as input and outputs generated answers, making it ideal for applications requiring automated customer support or information retrieval.

Canonical page: https://skillsregistry.net/skills/chowgi-glean-rag-mcp  
JSON: https://api.skillsregistry.net/v1/skills/chowgi-glean-rag-mcp

## Description

Enables answering natural-language questions from FAQ documents using vector search and LLM generation via an MCP tool.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/o62y9td2q1)
- **Repository:** <https://github.com/chowgi/glean-rag-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": "chowgi-glean-rag-mcp"
    }
  }
}
```

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