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mcp_chatbot vs filesystem

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

mcp_chatbot
by keli-wen
filesystem
by modelcontextprotocol
Stars★ 247★ 85,748
30d uses
Score4677
Official
Categories
AI / LLM ToolsDeveloper ToolsProductivity
File SystemDeveloper ToolsProductivity
LanguagePythonTypeScript
Last commit10 mo agothis month

mcp_chatbot · Summary

A Python chatbot implementation compatible with MCP, supporting terminal and Streamlit interfaces with customizable LLM integration.

filesystem · Summary

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

mcp_chatbot · Use cases

  • Building chatbot applications with MCP tool integration capabilities
  • Creating interactive terminal interfaces with LLM and MCP tool support
  • Developing web-based chatbots with real-time streaming responses and tool visualization

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

mcp_chatbot · Install

Installation

  1. Clone the repository:
git clone git@github.com:keli-wen/mcp_chatbot.git
cd mcp_chatbot
  1. Set up virtual environment and install dependencies:
pip install uv
uv venv .venv --python=3.10
source .venv/bin/activate  # or .venv\Scripts\activate for Windows
uv pip install -r requirements.txt
  1. Configure environment:
cp .env.example .env
# Edit .env with your API keys and paths
  1. Configure MCP servers in mcp_servers/servers_config.json

For Claude Desktop, add to claude_desktop_config.json:

{
  "mcpServers": {
    "mcp_chatbot": {
      "command": "python",
      "args": ["-m", "mcp_chatbot.server"]
    }
  }
}

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.