Which integrations are available for this server?

Allows Hugging Face models to access file operations and other tools through the MCP client library Supports local model integration through Ollama, providing access to file operations and other tools Enables OpenAI models to utilize the MCP server's tools including file operations via the MCP client

How do I use Universal MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Universal MCP Server read the contents of my notes.txt file" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCP Server - From Scratch

A Model Context Protocol (MCP) server implementation developed from scratch. When I say scratch I literally mean, that the JSON-RPC, STDIO, and server to client connection is written by hand! This is not a simple implementation that uses the @mcp.tool functionality you see online.

This project was created to help me understand the MCP protocol and was carefully modeled after the official MCP server specification.

Project Goals

Simple Architecture: Clean, from-scratch implementation following official MCP specification
Extensible Tools: Easy to add new tools and capabilities
Learning-Focused: Well-documented code to understand MCP internals

Related MCP server: MCP Local File Reader

Architecture

┌─────────────────┐    JSON-RPC     ┌─────────────────┐
│   AI Model      │ ◄──────────────► │   MCP Server    │
│ (Any Provider)  │     (stdio)     │   (Python)      │
└─────────────────┘                 └─────────────────┘
                                            │
                                            ▼
                                    ┌─────────────────┐
                                    │     Tools       │
                                    │ • File Reader   │
                                    │ • File Writer   │
                                    │ • Directory Ops │
                                    └─────────────────┘

Quick Start

Running the MCP Server

# Create virtual environment
python3 -m venv mcp-venv

# Activate virtual environment
source mcp-venv/bin/activate  # On macOS/Linux
# or
mcp-venv\Scripts\activate     # On Windows

# Install required packages
pip install -r requirements.txt

# Test server starts correctly
python3 src/mcp_server.py

Integrating with Models

Claude Desktop Config

For Claude Desktop, create or edit the config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Add the following configuration to claude_desktop_config.json:

{
  "mcpServers": {
    "barebones-server": {
      "command": "{project_path}/mcp-venv/bin/python",
      "args": ["{project_path}/src/mcp_server.py"],
      "env": {
        "PYTHONPATH": "{project_path}/src"
      }
    }
  }
}

Demo:

https://github.com/user-attachments/assets/d7e21bb3-bc6d-4b9b-8b7d-ed90f7f004fd

Available Tools

Current Tools

greeting: Returns a greeting message
read_file: Read contents of a file within allowed paths
write_file: Write content to files
list_directory: List files and folders in a directory
create_directory: Create a new directory

Testing

Run with MCP Inspector

# Install MCP Inspector globally
npm install -g @modelcontextprotocol/inspector
# Run the MCP server with Inspector
npx @modelcontextprotocol/inspector \
  /{path_to_MCP_projecct}/mcp-venv/bin/python \
  /{path_to_MCP_projecct}/src/mcp_server.py

Unit Tests

python -m __tests__.main

This server cannot be installed

-

security - not tested

F

license - not found

-

quality - not tested

How are these scores calculated?

Resources

GitHub Repository

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Universal MCP Server