RAG for your documents

Name: RAG for your documents
Author: DevilsDev

by DevilsDevversion 3.7.0i★ –iRuns on your computer

Registry nameio.github.DevilsDev/rag-mcp-server

Install

Overview

Description from the maker (original English)

Search a folder of documents and check answers against them. Offline: no API key or database.

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 checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

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 on your computer
Transport: stdio
Category: Search & AI memory

Install

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

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

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

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "rag": {
      "command": "npx",
      "args": [
        "-y",
        "@devilsdev/rag-mcp-server"
      ]
    }
  }
}

Run this in your terminal

claude mcp add rag -- npx -y @devilsdev/rag-mcp-server

This one needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

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

{
  "mcpServers": {
    "rag": {
      "command": "npx",
      "args": [
        "-y",
        "@devilsdev/rag-mcp-server"
      ]
    }
  }
}

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 one needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "rag": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@devilsdev/rag-mcp-server"
      ]
    }
  }
}

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 one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

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

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

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

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 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account DevilsDev, 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
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7223 servers in this category
Published to the registry more recently than 100% of the other 7223 servers in this category
Basic checks equal to or better than 100% of the other 7223 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 RAG for your documents safe?

It passed 1 of 1 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?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (3.7.0) reached the registry today.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

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:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

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

Computer or cloud★ 64,224MITUpdated 3 days ago

Install

Codebase Memory

by DeusData

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

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

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

Runs in the cloud★ 5,213MITUpdated 44 days ago

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.

@devilsdev/rag-mcp-server

An MCP server for your documents. Point it at a folder and Claude, or any other MCP client, can search the documents and check answers against them:

npx @devilsdev/rag-mcp-server ./docs

It indexes the folder when it starts, with the offline TF-IDF embedder and an in-memory retriever from @devilsdev/rag-pipeline-utils. It needs no API key, no database and no network. The assistant is the language model, so the server never calls one.

Requires Node.js 22 or later.

Connect a client

The server speaks MCP over stdio, so the client starts it. Use an absolute path to your folder.

Claude Code:

claude mcp add docs -- npx -y @devilsdev/rag-mcp-server /absolute/path/to/docs

Claude Desktop, Cursor and other clients that use an mcpServers config (for Claude Desktop: Settings → Developer → Edit Config, then restart):

"mcpServers": { "docs": { "command": "npx", "args": ["-y", "@devilsdev/rag-mcp-server", "/absolute/path/to/docs"] } } }

Then ask something your documents answer, such as "How many vacation days do employees get?".

Tools

`search_documents`

Input	Type	Description
`query`	string, required	What to look for, in natural language
`topK`	integer, 1–20	Passages to return (default 4, or `--top-k`)

Returns { passages: [{ id, source, score, text }] }, best first, as structured content and as JSON text. source is the file relative to the folder and id is # . Passages that share no terms with the query are left out.

`check_answer`

Input	Type	Description
`answer`	string, required	The answer to check
`question`	string	The question it answers; improves retrieval when `sources` is omitted
`sources`	array of strings or `{ id, text }`	Passages to check against; omit to search the indexed documents
`topK`	integer, 1–20	Passages to retrieve when `sources` is omitted

Runs the library's checkAnswer and returns { grounded, groundedness, unsupported, citations, sources }: whether every sentence is supported, the share of supported sentences (0 to 1), the unsupported sentences, the ids of the sources supporting each sentence, and the sources that were checked. The check is lexical and makes no model calls, so a correct paraphrase can come back unsupported; treat it as a flag to look again, not a verdict.

Both tools are read-only. Passage text is content from your files, and the tool descriptions tell the client to treat it as data, not instructions. A file can still contain text written to manipulate an assistant, so index folders you trust.

Files

Markdown (.md, .markdown), HTML (.html, .htm, visible text only), CSV (.csv, one passage per row) and text (.txt) files, in the folder and its subfolders, handled the way the library's loaders handle them; prose is split into sentence chunks of up to 500 characters. Other files, node_modules and .git are skipped. The index lives in memory and is rebuilt each time the server starts, so restart the client's server after changing the documents.

Options

rag-mcp-server <folder> [--top-k <n>] [--embedder local]

Option	Default	Meaning
`--top-k`	`4`	Passages per call when the client doesn't pass `topK`
`--embedder`	`local`	The embedder; `local` (TF-IDF, offline) is the only one

Everything the server logs goes to stderr; stdout carries the protocol.

Build your own

For other embedders (OpenAI, Ollama), a persistent index or a vector database, start from the MCP server example, which builds the same kind of server from the library in about 100 lines.

Documentation: https://devilsdev.github.io/rag-pipeline-utils/

RAG for your documents

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

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

@devilsdev/rag-mcp-server

Connect a client

Tools

search_documents

check_answer

Files

Options

Build your own

`search_documents`

`check_answer`