filesystem vs ramibot

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

	filesystem by modelcontextprotocol	ramibot by RamiBotAI
Stars	★ 85,748	★ 20
30d uses	—	—
Score	77	43
Official	✓	—
Categories	File SystemDeveloper ToolsProductivity	SecurityDeveloper ToolsAI / LLM Tools
Language	TypeScript	Python
Last commit	this month	2 mo ago

filesystem · Summary

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

ramibot · Summary

RamiBot is a local-first AI security platform with MCP integration for red/blue team operations.

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

ramibot · Use cases

Red team operations with LLM-assisted vulnerability scanning
Blue team analysis with evidence-locked reporting
Security research with Docker-contained tool execution

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.

ramibot · Install

Installation

**Requirements:** Python 3.9+, Node.js 18+, npm, Docker Desktop

**One-command install (recommended):**

git clone <repository-url>
cd ramibot

# Linux / macOS
bash install.sh

# Windows
install.bat

**Manual install:**

Clone and navigate to the repository
Backend: cd backend; python -m venv .venv; .venv\Scripts\activate (Windows) or source .venv/bin/activate (Unix); pip install -r requirements.txt
Frontend: cd frontend; npm install
Run: bash start.sh (Unix) or start.bat (Windows)

**Settings:** Edit backend/settings.json to add your API keys.

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