Allows listing repository commits and authenticates using GitHub Personal Access Token.
Enables place search functionality with configurable search radius using the Google Maps API.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP (Model Context Protocol) Server calculate the distance between New York and Los Angeles"
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.
This repository demonstrates the usage of Model Context Protocol (MCP) with various integrations including a custom calculator server, GitHub, and Google Maps.
Model Context Protocol (MCP) is a protocol that enables AI models to interact with external tools and services. It provides a standardized way for AI models to:
Execute tools and functions
Access resources
Generate prompts
Interact with external services
Related MCP server: MCP Server Demo
├── server.py # MCP server (custom creation)
├── client_server.py # MCP Client
├── 1)maps.py # Google Maps MCP integration
├── 2)github.py # GitHub MCP integration
└── requirements.txt # Project dependencies
Implements basic arithmetic operations
Demonstrates MCP tool creation
Shows resource and prompt handling
List repository commits
Uses GitHub Personal Access Token for authentication
Demonstrates environment variable handling
Search for places using Google Maps API
Configurable search radius
Environment variable based API key management
Install dependencies:
pip install -r requirements.txt
Tools: Functions that perform specific actions
Defined using @mcp.tool decorator
Can accept parameters and return values
Resources: Static or dynamic data sources
Defined using @mcp.resource decorator
Accessed using resource URLs
Prompts: Template-based text generation
Defined using @mcp.prompt decorator
Can include dynamic content
Always use environment variables for sensitive data
Implement proper error handling
Use type hints for better code clarity
Document your tools with clear docstrings
Keep API keys secure and never commit them to version control
@mcp.tool(name="add")
def add(a: int, b: int):
return a + b
Running server.py file, it will up and run the MCP server.
result = await session.call_tool("add", arguments={"a": 5, "b": 3})
Running client_server.py file, it will connect to the MCP server.
This server cannot be deployed
A comprehensive Model Context Protocol (MCP) server that enables AI assistants to interact with yo…
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A Model Context Protocol server for Wix AI tools
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