qurio vs filesystem

Side-by-side comparison to help you pick between these two MCP servers.

	qurio by irahardianto	filesystem by modelcontextprotocol
Stars	★ 16	★ 85,748
30d uses	—	—
Score	41	77
Official	—	✓
Categories	AI / LLM ToolsDeveloper ToolsKnowledge Graph	File SystemDeveloper ToolsProductivity
Language	Go	TypeScript
Last commit	3 mo ago	this month

qurio · Summary

A self-hosted RAG engine for AI coding assistants that ingests technical docs and code repositories locally, serving grounded context via MCP to prevent hallucinations.

filesystem · Summary

A feature-rich MCP server for filesystem operations with dynamic directory access control.

qurio · Use cases

Providing accurate, context-aware responses for AI coding assistants like Cursor, Claude Code, or Gemini CLI
Creating a private knowledge base for proprietary documentation and internal code repositories
Enhancing AI productivity by reducing hallucinations through grounded context retrieval

filesystem · Use cases

Enable AI models to read and write project files during development
Allow Claude or other MCP clients to browse and analyze codebases
Provide secure sandboxed access to specific directories for content generation

qurio · Install

Installation

Prerequisites

[Docker](https://docs.docker.com/get-docker/) and [Docker Compose](https://docs.docker.com/compose/install/)
A [Google Gemini API Key](https://aistudio.google.com/app/apikey) (for embeddings)

Steps

Clone the repository:

``bash git clone https://github.com/irahardianto/qurio.git cd qurio ``

Configure environment:

``bash cp .env.example .env # Add your Gemini API key to .env ``

Start the system:

``bash docker-compose up -d ``

Access the dashboard at http://localhost:3000
Add additional API keys (Jina AI/Cohere) in the settings page

MCP Configuration

Add to your MCP settings:

{
  "mcpServers": {
    "qurio": {
      "httpUrl": "http://localhost:8081/mcp"
    }
  }
}

filesystem · Install

Installation

Using NPX

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/path/to/allowed/directory"
      ]
    }
  }
}

Using Docker

{
  "mcpServers": {
    "filesystem": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--mount", "type=bind,src=/path/to/allowed/dir,dst=/projects/allowed/dir",
        "mcp/filesystem",
        "/projects"
      ]
    }
  }
}

VS Code Extension

Click the installation buttons in the README to install directly in VS Code.

Comparison generated from public README + GitHub signals. Last updated automatically.