filesystem vs LLaMa-MCP-Streamlit

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

	filesystem by modelcontextprotocol	LLaMa-MCP-Streamlit by Nikunj2003
Stars	★ 85,748	★ 43
30d uses	—	—
Score	77	36
Official	✓	—
Categories	File SystemDeveloper ToolsProductivity	AI / LLM ToolsDeveloper ToolsProductivity
Language	TypeScript	Python
Last commit	this month	15 mo ago

filesystem · Summary

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

LLaMa-MCP-Streamlit · Summary

A Streamlit AI assistant using MCP to enable tool interactions with LLaMa 3.3 or Ollama models.

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

LLaMa-MCP-Streamlit · Use cases

Creating an interactive chat interface that can execute commands via MCP
Building a custom AI assistant with access to file system tools
Developing a prototype for LLM applications with external tool integration

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.

LLaMa-MCP-Streamlit · Install

Installation Steps

Clone the repository
Set up environment variables in .env file:

```bash # NVIDIA NIM API API_ENDPOINT=https://integrate.api.nvidia.com/v1 API_KEY=your_api_key_here

# Ollama API_ENDPOINT=http://localhost:11434/v1/ API_KEY=ollama ```

Install dependencies using Poetry:

``bash poetry install ``

Run the Streamlit app:

``bash poetry run streamlit run llama_mcp_streamlit/main.py ``

To use with Claude Desktop, add to claude_desktop_config.json:

{
  "mcpServers": {
    "llama-mcp-streamlit": {
      "command": "python",
      "args": ["path/to/llama_mcp_streamlit/utils/mcp_server.py"]
    }
  }
}

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