#python #anthropic #api #claude #llm #model_context_protocol #python #server

FastMCP is a tool that helps developers build servers for AI applications using the Model Context Protocol (MCP). It makes it easy to create tools, expose data, and define interaction patterns for AI models. With FastMCP, you can focus on building great tools without worrying about complex protocol details. It's fast, simple, and uses Pythonic code, making it easy for developers to integrate AI with various data sources and tools. This simplifies AI development and makes it more efficient.

https://github.com/jlowin/fastmcp

#python #agents #ai #ai_agents #llm #llms #mcp #model_context_protocol #python

The Model Context Protocol (MCP) is a standard way for AI agents to connect with different tools and data sources, making it much easier to build powerful AI applications without writing custom code for each integration[2][5]. The mcp-agent framework uses MCP to let you quickly create agents that can do things like read files, fetch web pages, or manage emails, and you can combine these agents in flexible ways to handle complex tasks. This means you can focus on what you want your AI to do, while mcp-agent takes care of connecting to the right tools and managing the workflow, saving you time and effort[3][5].

https://github.com/lastmile-ai/mcp-agent

#python #csharp #java #javascript #javascript_applications #mcp #mcp_client #mcp_security #mcp_server #model #model_context_protocol #modelcontextprotocol #python #typescript

You can learn the Model Context Protocol (MCP), a new standard for connecting AI models with applications, through a free, open-source curriculum that includes hands-on coding examples in C#, Java, JavaScript, Python, and TypeScript. The curriculum covers basics, security, building servers and clients, advanced topics, and best practices, with multi-language support and community help via Discord. You can also join MCP Dev Days, a free online event for deep technical learning and networking. This resource helps you quickly gain practical skills to build and integrate AI tools effectively, boosting your development capabilities in AI workflows.

https://github.com/microsoft/mcp-for-beginners

#python #agents #ai #api_gateway #asyncio #authentication_middleware #devops #docker #fastapi #federation #gateway #generative_ai #jwt #kubernetes #llm_agents #mcp #model_context_protocol #observability #prompt_engineering #python #tools

The MCP Gateway is a powerful tool that unifies different AI service protocols like REST and MCP into one easy-to-use endpoint. It helps you manage multiple AI tools and services securely with features like authentication, retries, rate-limiting, and real-time monitoring through an admin UI. You can run it locally or in scalable cloud environments using Docker or Kubernetes. It supports various communication methods (HTTP, WebSocket, SSE, stdio) and offers observability with OpenTelemetry for tracking AI tool usage and performance. This gateway simplifies connecting AI clients to diverse services, making development and management more efficient and secure.

https://github.com/IBM/mcp-context-forge

#other #ai #anthropic_claude #awesome #context #mcp #model_context_protocol #servers #tool_use #tools

Model Context Protocol (MCP) is an open standard that lets AI models securely connect to various data sources and tools, like files, databases, APIs, and cloud services, to get real-time, relevant information. This helps AI give more accurate, up-to-date, and context-aware answers, reducing repeated data processing and improving efficiency. MCP also supports automation of complex workflows and integration with many platforms, making AI more powerful and flexible. However, running MCP servers requires careful security measures to avoid risks like unauthorized code execution. Using MCP can save time, reduce costs, and enhance AI capabilities for tasks like chatbots, data analysis, and system control.

https://github.com/appcypher/awesome-mcp-servers