MCP Playground
A playground for MCP implementations featuring multiple microservices, including news and weather examples.
MCP Playground
Table of Contents
- Description
- Requirements
- Technologies and Tools
- Local Installation Instructions
- Available Make Commands
- Connecting with Claude Desktop
Description
This project is a playground for MCP (Model Context Provider) implementations, featuring multiple microservices including a News MCP and Weather MCP. The services are implemented using MCP with stdio transport, providing a simple and efficient way to expose functionality through standard input/output streams.
Requirements
- Python 3.12
uvpackage manager- Virtual environment support
Technologies and Tools
mcp[cli]: Model Context Provider for service communicationhttpx: Modern HTTP client for Pythonpython-dotenv: Environment variable management
Local Installation Instructions
- Clone the repository:
git clone https://github.com/RonFelsenfeld/mcp-playground.git
cd mcp-playground
- Set up the virtual environment and install dependencies:
make setup
- Activate the virtual environment:
source .venv/bin/activate
- Sync dependencies:
make sync
-
Run the MCP services:
- To run the News MCP service:
python -m src.news_mcp.main- To run the Weather MCP service:
python -m src.weather_mcp.main
Available Make Commands
make setup: Creates a new virtual environmentmake activate: Shows activation command for the virtual environmentmake sync: Syncs project dependenciesmake freeze-dependencies: Freezes current dependencies to requirements.txtmake clean: Removes virtual environment and lock files
Connecting with Claude Desktop
This project can be connected to Claude Desktop to test and interact with the MCP services using Anthropic's Model Context Protocol (MCP).
-
Install Claude Desktop, available here
-
Open Claude, go to Settings -> Developer
-
Click "Edit Config"
-
Open "claude_desktop_config.json" file
-
Copy-paste the following JSON inside the file:
{
"mcpServers": {
"weather": {
"command": "<ABSOLUTE_PATH_TO_UV>",
"args": [
"--directory",
"<YOUR_PROJECT_PATH>",
"run",
"-m",
"src.weather_mcp.main"
]
},
"news": {
"command": "<ABSOLUTE_PATH_TO_UV>",
"args": [
"--directory",
"<YOUR_PROJECT_PATH>",
"run",
"-m",
"src.news_mcp.main"
],
"env": {
"NEWS_API_KEY": "<YOUR_NEWS_API_KEY>"
}
}
}
}
Replace:
<ABSOLUTE_PATH_TO_UV>with the absolute path to youruvexecutable (from thewhich uvcommand)<YOUR_PROJECT_PATH>with the absolute path to your project directory
For the News MCP service, you'll need a News API key from newsdata.io. You can get a free API key by:
- Creating an account at newsdata.io
- Going to your dashboard
- Generating a new API key
After generating you API key, replace <YOUR_NEWS_API_KEY> with it.
Похожие серверы
Scout Monitoring MCP
спонсорPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
спонсорAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
gopls-mcp
The essential MCP server for Go language: Exposing compiler-grade semantics to AI Agents and LLM for deterministic code analysis and minimal token usage.
CocoaPods Package README
Retrieve README files and package information from CocoaPods.
EDUCHAIN Agent Kit
Provides tools for interacting with the EDUCHAIN blockchain, including wallet, swap, and arbitrage operations on SailFish DEX.
Devvit
A companion server for building applications on Reddit's developer platform.
Web3 MCP Server
An MCP server for interacting with Web3 and EVM-compatible chains.
MCP Android Agent
Automate Android devices using the uiautomator2 library, requiring adb and a connected device.
OpenAI GPT Image
Generate and edit images using OpenAI's GPT-4o image generation and editing APIs with advanced prompt control.
MCP Code Graph
Analyze and visualize code graphs using CodeGPT.
MCP Todo Server
A demo Todo application server built with a clean architecture using MCPServer and JSON Placeholder.
DINO-X
Advanced computer vision and object detection MCP server powered by Dino-X, enabling AI agents to analyze images, detect objects, identify keypoints, and perform visual understanding tasks.