# FAQ RAG MCP Server

> Use this tool when you need to efficiently search and retrieve relevant information from large collections of FAQ documents, or generate answers to user queries based on semantic similarity. It solves problems of information overload and manual search by providing accurate and context-specific results. The FAQ RAG MCP Server takes in natural language queries and returns relevant answers, making it ideal for applications requiring intuitive and informative user interactions.

Canonical page: https://skillsregistry.net/skills/rhamsagar-sf-rag-mcp-project  
JSON: https://api.skillsregistry.net/v1/skills/rhamsagar-sf-rag-mcp-project

## Description

Enables semantic search and question-answering over FAQ documents using RAG (Retrieval-Augmented Generation) with OpenAI embeddings and in-memory vector similarity.

## Trust

- **Trust score (0–1):** 0.83
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/joepfo1yll)
- **Repository:** <https://github.com/rhamsagar-sf/rag-mcp-project>

## 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": "rhamsagar-sf-rag-mcp-project"
    }
  }
}
```

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