This template provides a streamlined foundation for developing Model Context Protocol (MCP) servers in Python, incorporating integrated documentation, cursor rules, and example implementations to simplify AI tool development.
Added on:
Created by:
Mar 20 2025
This template provides a streamlined foundation for developing Model Context Protocol (MCP) servers in Python, incorporating integrated documentation, cursor rules, and example implementations to simplify AI tool development.
Added on:
Created by:
Mar 20 2025
Sontal/Sun Hui
Featured
What is Model Context Protocol Server Template?
The MCP Server Python Template is designed to enable efficient and standardized creation of MCP servers in Python. It includes a ready-to-use server implementation, configurable transport modes like stdio and SSE, embedded MCP specifications, and example services such as a weather API. The template emphasizes clean, well-documented code, minimal dependencies, and comprehensive MCP documentation within the project. It supports AI-assisted development by providing built-in cursor rules and detailed resource guides, making it easier for developers and AI tools to understand MCP concepts, implement custom tools, and deploy robust MCP solutions.
Who will use Model Context Protocol Server Template?
- AI developers working with MCP
- Backend developers creating MCP tools
- AI researchers interested in MCP integrations
- Automation engineers building MCP-based systems
How to use the Model Context Protocol Server Template?
- Step 1: Clone the repository from GitHub
- Step 2: Create a virtual environment and install dependencies
- Step 3: Use `server.py` to run the MCP server with desired transport mode
- Step 4: Define custom MCP tools by importing and decorating functions with `@mcp.tool()`
- Step 5: Deploy and integrate MCP server with relevant AI applications or services
Model Context Protocol Server Template's Core Features & Benefits
The Core Features
- Embedded MCP specifications
- Configurable transport modes (stdio, SSE)
- Example service integrations (weather API)
The Benefits
- Facilitates rapid MCP server development
- Supports AI-assisted coding and resource understanding
- Well-documented and minimal dependency setup
Model Context Protocol Server Template's Main Use Cases & Applications
- Developing custom MCP tools for AI models
- Building MCP-compliant services for automation
- Integrating MCP servers with AI and web applications
FAQs of Model Context Protocol Server Template
Developer
- sontallive
You may also like:
Developer Tools
A desktop application for managing server and client interactions with comprehensive functionalities.
A Model Context Protocol server for Eagle that manages data exchange between Eagle app and data sources.
A chat-based client that integrates and uses various MCP tools directly within a chat environment for enhanced productivity.
A Docker image hosting multiple MCP servers accessible through a unified entry point with supergateway integration.
Provides access to YNAB account balances, transactions, and transaction creation through MCP protocol.
A fast, scalable MCP server for managing real-time multi-client Zerodha trading operations.
A remote SSH client facilitating secure, proxy-based access to MCP servers for remote tool utilization.
A Spring-based MCP server integrating AI capabilities for managing and processing Minecraft mod communication protocols.
A minimalistic MCP client with essential chat features, supporting multiple models and contextual interactions.
A secure MCP server enabling AI agents to interact with Authenticator App for 2FA codes and passwords.
Research And Data
A server implementation supporting Model Context Protocol, integrating CRIC's industrial AI capabilities.
Provides real-time traffic, air quality, weather, and bike-sharing data for Valencia city in a unified platform.
A React application demonstrating integration with Supabase via MCP tools and Tambo for UI component registration.
A MCP client integrating Brave Search API for web searches, utilizing MCP protocol for efficient communication.
A protocol server enabling seamless communication between Umbraco CMS and external applications.
NOL integrates LangChain and Open Router to create a multi-client MCP server using Next.js
Connects LLMs to Firebolt Data Warehouse for autonomous querying, data access, and insight generation.
A client framework for connecting AI agents to MCP servers, enabling tool discovery and integration.
Spring Link facilitates linking and managing multiple Spring Boot applications efficiently within a unified environment.
An open-source client to interact with multiple MCP servers, enabling seamless tool access for Claude.
AI Chatbot
Integrates APIs, AI, and automation to enhance server and client functionalities dynamically.
Provides long-term memory for LLMs by storing and retrieving contextual information via MCP standards.
An advanced clinical evidence analysis server supporting precision medicine and oncology research with flexible search options.
A platform collecting A2A agents, tools, servers, and clients for effective agent communication and collaboration.
A Spring-based chatbot for Cloud Foundry that integrates with AI services, MCP, and memGPT for advanced capabilities.
An AI agent controlling macOS using OS-level tools, compatible with MCP, facilitating system management via AI.
PHP client library enabling interaction with MCP servers via SSE, StdIO, or external processes.
A platform for managing and deploying autonomous agents, tools, servers, and clients for automation tasks.
Enables interaction with powerful Text to Speech and video generation APIs for multimedia content creation.
An MCP server providing API access to RedNote (XiaoHongShu, xhs) for seamless integration.