MiniRAG

Name: MiniRAG
Author: KiMelody

by KiMelodyversion 0.1.0i★ –iRuns in the cloud

Registry nameio.github.KiMelody/minirag

Install

Overview

Description from the maker (original English)

Lightweight self-hosted RAG knowledge base with hybrid retrieval and cited answers.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi2 of 3 passedChecked from public information; code not scanned yet
UsageiVery new★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs in the cloud
Transport: SSE
Category: Search & AI memory
You need to fill in: Authorization

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 2 of 3 passed
Runs on the maker’s server: what you ask it goes through their server.
You fill in yourself: Authorization

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

Runs in the cloudNothing to install; it connects over the internet

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Run this in your terminal

claude mcp add --transport sse minirag https://minirag.kimelody.de5.net/sse --header 'Authorization: your-value'

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "minirag": {
      "url": "https://minirag.kimelody.de5.net/sse",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "minirag": {
      "type": "sse",
      "url": "https://minirag.kimelody.de5.net/sse",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

Authorization secret required HTTP header
HTTP Basic auth: 'Basic ' + base64('demo: '). Request the access key from the repo owner (see README).

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

The server asks you to sign in before it lists its tools.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account KiMelody, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
✓ Pass
Endpoint responds
Responded in 848 ms (HTTP 401)
! Caution
Sign-in with OAuth
Needs a key or token that you copy and paste yourself
… Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint

Compared with others in Search & AI memoryi

More stars than 0% of the other 5692 servers in this category
Published to the registry more recently than 63% of the other 5692 servers in this category
Basic checks equal to or better than 39% of the other 5692 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is MiniRAG safe?

It passed 2 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: Authorization

Does it run on my computer or in the cloud?

It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.0) reached the registry 24 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

by upstashWidely used↓ 972.7K/wk★ 64.2KUpdated 2 days ago

Computer or cloud

Install

Codebase Memory

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

by DeusDataWidely used↓ 18K/wk★ 48.1KUpdated 22 days ago

Runs on your computer

Install

Exa

Connect AI agents to Exa for web search, content fetching, and multi-step research.

by exa-labsGrowing★ 5.2KUpdated 2 months ago

Runs in the cloud✓ exa.ai

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

MiniRAG

A self-hosted RAG knowledge base in a single Spring Boot process: SQLite storage, hybrid retrieval, cited answers, and a built-in MCP server. No vector database, no message queue.

Live demo (ask the owner for the access code) · Evaluation report

Features

Hybrid retrieval — in-memory cosine + SQLite FTS5 (BM25), fused with RRF; optional LLM rerank
Cited answers — clickable [n] citations; only sources actually cited are displayed
Streaming web UI — SSE, typewriter rendering, markdown, retrieval-mode switcher (vector / hybrid / rerank)
Small footprint — single process, ~250MB RSS, runs on a 1GB VPS
Multiple interfaces — MCP server (SSE transport), REST API, web UI, WeChat Work callback integration

Quick start

docker run -d --name minirag -p 18090:18090 --memory 512m \

-v $(pwd)/data:/app/data \ -e DEEPSEEK_API_KEY=sk-... \ -e EMBEDDING_API_KEY=sk-... \ ghcr.io/kimelody/minirag:latest

Open http://localhost:18090 and start asking. Data lives in ./data (SQLite, created automatically).

Configuration

Env	Required	Default	Description
`DEEPSEEK_BASE_URL`	no	`https://api.deepseek.com`	Any OpenAI-compatible chat endpoint
`DEEPSEEK_API_KEY`	yes	—	Chat model API key
`EMBEDDING_BASE_URL`	no	`https://api.siliconflow.cn/v1`	OpenAI-compatible embeddings endpoint
`EMBEDDING_API_KEY`	yes	—	Embeddings API key
`EMBEDDING_MODEL`	no	`BAAI/bge-m3`	Embedding model
`DEMO_KEY`	no	—	Visitor access code for read APIs; unset = open (local dev)
`ADMIN_KEY`	no	—	Admin key required for ingest APIs

MCP

Listed on the official MCP Registry as io.github.KiMelody/minirag. Two tools: query(question, mode?) — ask and get a cited answer; ingest_text(docId, text, adminKey) — add a document.

claude mcp add --transport sse minirag http://localhost:18090/sse

"mcpServers": { "minirag": { "url": "http://localhost:18090/sse" } } }

The hosted demo endpoint requires basic auth: https://minirag.kimelody.de5.net/sse (ask the owner for credentials).

REST API

Method	Path	Description
POST	`/api/chat`	Ask; returns answer + cited sources (JSON)
POST	`/api/chat/stream`	Same, streamed as SSE (`meta` / `token` / `sources` / `done`)
GET	`/api/search?q=&mode=`	Retrieval debug: `vector` \	`hybrid` \	`rerank`
POST	`/api/documents/text`	Ingest `{docId, text}` (requires `X-Admin-Key`)
POST	`/api/documents`	Ingest an uploaded file, multipart (requires `X-Admin-Key`)

Evaluation

An eval harness ships in eval/: labeled question sets, Top-1 / Recall / MRR scoring over three retrieval modes — hybrid+rerank reaches Top-1 100% / MRR 1.0 on the demo set (report); a 20-question labor-law evaluation with corpus-cleaning scripts lives in eval/law/. Bring your own corpus; raw source texts are not redistributed.

Build from source

mvn package

java -jar target/minirag-0.1.0-SNAPSHOT.jar

Requires Java 21. API keys can be put in a .env file in the working directory (git-ignored).

中文说明

单进程私有化 RAG 知识库：SQLite 存储 + 混合检索（向量 + BM25，RRF 融合，可选 LLM 重排），回答带可点击引用角标，自带网页演示、REST API 与 MCP server（SSE），内存占用约 250MB，1GB 小服务器可跑。在线演示（访问码联系作者）。

License

MIT

MiniRAG

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

MiniRAG

Features

Quick start

Configuration

MCP

REST API

Evaluation

Build from source

中文说明

License