# BigQuery RAG MCP Server

> BigQuery RAG MCP Server — shrprabh-bigquery-rag-mcp. Use this tool when you need to convert natural-language questions into structured passages with relevant metadata, or when building a document-grounded chatbot that requires semantic retrieval over large document collections. It takes in natural-language questions as input and returns structured passages with source and page metadata as output. Ideal for applications requiring efficient and accurate information retrieval from large datasets stored in BigQuery.

Canonical page: https://skillsregistry.net/skills/shrprabh-bigquery-rag-mcp  
JSON: https://api.skillsregistry.net/v1/skills/shrprabh-bigquery-rag-mcp

## Description

A private MCP server that converts natural-language questions into embeddings and performs semantic retrieval over document chunks stored in BigQuery, returning structured passages with source and page metadata. It serves as the read-only retrieval layer for a document-grounded chatbot.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/d4fw0ncwu0)
- **Repository:** <https://github.com/shrprabh/bigquery-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": "shrprabh-bigquery-rag-mcp"
    }
  }
}
```

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