About Model Context Protocol Client Server
Model Context Protocol Client Server is an MCP server published by SaiDurga98 in the Developer Tools category: this repo has Model Context Protocol (MCP), focusing on building both MCP servers and clients using the Python SDK.
Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/SaiDurga98/Model-Context-Protocol-Client-Server-This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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README
Model-Context-Protocol-Client-Server
This repo has comprehensive coverage of the Model Context Protocol (MCP), focusing on building both MCP servers and clients using the Python SDK. You'll learn about MCP's three core primitives—tools, resources, and prompts—and understand how they integrate with Claude AI to create powerful applications without writing extensive integration code.
What we can learn 1.Understand MCP architecture and how it shifts tool definition and execution burden from your server to specialized MCP servers 2.Learn about MCP's transport-agnostic communication system and the message types used between clients and servers 3.Explore the complete request-response flow from user queries through MCP clients to external services and back to Claude 4.Build MCP servers using the Python SDK with decorators to define tools instead of writing JSON schemas manually 5.Implement document management functionality with tools for reading and editing documents using Field descriptions and type hints 6.Use the built-in MCP Server Inspector to test and debug your server functionality in a browser-based interface 7.Define resources for exposing read-only data, including both direct resources with static URIs and templated resources with parameters 8.Implement resource reading functionality in clients with proper MIME type handling for JSON and text content 9.Build prompts that provide pre-crafted, high-quality instructions for common workflows like document formatting 10.Understand when to use each MCP primitive: tools (model-controlled), resources (app-controlled), and prompts (user-controlled) 11.Examine practical integration patterns including autocomplete functionality and context injection for AI conversations
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.