# Gemini RAG MCP Server

> Use this tool when you need to create and query knowledge bases using large document collections, and want to enable AI applications to retrieve information and generate text based on uploaded documents. It solves problems related to information retrieval, document search, and text generation, by providing a scalable and efficient way to manage and query large knowledge bases. The tool accepts document uploads as input and returns relevant information and generated text as output, making it ideal for use cases where AI applications require access to large amounts of structured and unstructured data.

Canonical page: https://skillsregistry.net/skills/masseater-gemini-rag-mcp  
JSON: https://api.skillsregistry.net/v1/skills/masseater-gemini-rag-mcp

## Description

Enables creation and querying of knowledge bases using Google's Gemini API File Search feature, allowing AI applications to upload documents and retrieve information through RAG (Retrieval-Augmented Generation).

## Trust

- **Trust score (0–1):** 0.94
- **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/vimk59r1gl)
- **Repository:** <https://github.com/masseater/gemini-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": "masseater-gemini-rag-mcp"
    }
  }
}
```

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