gradio-mcp-server-builder

Build MCP Servers with Gradio: Your CLI Tool for Efficiency

Table of Contents

• Overview
• Features
• Installation
• Usage
• Examples
• Contributing
• License
• Support

Overview

The gradio-mcp-server-builder is a command-line interface (CLI) tool designed to simplify the creation of Model Context Protocol (MCP) servers. It integrates seamlessly with Gradio, allowing you to build web interfaces for your existing Python functions. This tool lets you focus on your core functionality, minimizing the need for boilerplate code.

For the latest releases, visit here.

Features

• Easy Setup: Quickly set up an MCP server with minimal configuration.
• Gradio Integration: Create user-friendly web interfaces for your Python functions.
• Flexible: Adapt the tool to various use cases, from simple scripts to complex applications.
• Lightweight: Focus on your code without unnecessary overhead.
• Community Driven: Open-source and welcomes contributions.

Installation

To install the gradio-mcp-server-builder, follow these steps:

1. Clone the Repository:

   git clone https://github.com/CoolBeans4477/gradio-mcp-server-builder.git
   cd gradio-mcp-server-builder
   

2. Install Dependencies: Ensure you have Python installed. Then, run:

   pip install -r requirements.txt
   

3. Run the Tool: After installation, you can start using the CLI tool.

For the latest release files, download and execute from here.

Usage

Basic Command

To create a new MCP server, use the following command:

python mcp_server_builder.py --function your_function_name

Replace your_function_name with the name of the Python function you want to expose via the web interface.

Options

• --function: Specify the function to expose.
• --port: Define the port number for the server (default is 7860).
• --title: Set a title for your Gradio interface.

Example

Here’s a simple example to demonstrate usage:

def greet(name):
    return f"Hello, {name}!"

# Save this function in a file named greet.py

# Command to run
python mcp_server_builder.py --function greet

This will create a web interface where users can input their name and receive a greeting.

Examples

Example 1: Simple Calculator

Create a simple calculator function and expose it:

def add(x, y):
    return x + y

# Run the command
python mcp_server_builder.py --function add

Example 2: Text Summarization

Using a language model to summarize text:

from transformers import pipeline

summarizer = pipeline("summarization")

def summarize(text):
    return summarizer(text)

# Run the command
python mcp_server_builder.py --function summarize

Example 3: Image Classification

Integrate an image classification model:

from torchvision import models, transforms
from PIL import Image

model = models.resnet50(pretrained=True)
model.eval()

def classify_image(image_path):
    image = Image.open(image_path)
    # Apply necessary transformations
    return model(image)

# Run the command
python mcp_server_builder.py --function classify_image

Contributing

We welcome contributions from the community. To contribute:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them.
4. Push to your fork and submit a pull request.

For detailed guidelines, check the CONTRIBUTING.md file in the repository.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Support

If you have any questions or need assistance, please check the Issues section of the repository.

For the latest release files, download and execute from here.

Topics

• agent: Explore how agents can interact with the MCP servers.
• agentic-ai: Understand the role of AI agents in this ecosystem.
• code-generation: Learn about automated code generation techniques.
• gradio: Discover the Gradio library for building interfaces.
• gradio-interface: Dive into creating Gradio interfaces.
• huggingface: Integrate models from Hugging Face.
• language-model: Work with various language models.
• mcp: Understand the Model Context Protocol.
• mcp-client: Learn how to build clients for MCP servers.
• mcp-server: Explore the server-side implementation of MCP.
• smolagents: Discover lightweight agents for various tasks.

Additional Resources

• Gradio Documentation
• Hugging Face Models
• Python Documentation

Acknowledgments

Thanks to the contributors and community members who make this project possible. Your feedback and support are invaluable.

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For the latest releases, visit here.