TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #14793 · Jun 5
#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
Search: #runtime
@golang · Post #58 · 04/22/2018, 08:22 PM
Why are goroutines not lightweight threads? Kartik Khare shows us his meaning about goroutines, lightweight threads and their difference in GoLang. There are no code examples inside but good thoughts about parallelism, threads and useful links at the end of the article :) #development#runtime#language https://codeburst.io/why-goroutines-are-not-lightweight-threads-7c460c1f155f
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@golang · Post #64 · 06/21/2018, 04:17 PM
Hi there! Which ways do you use to avoid memory leaks for REST API? In the following article by Iman Tumorang describes an excellent example of memory leaks, his solution, and results. Must have to read for everyone 😉 #development#runtime#architecture https://hackernoon.com/avoiding-memory-leak-in-golang-api-1843ef45fca8
@githubtrending · Post #15382 · 01/01/2026, 12:30 PM
#jupyter_notebook#agent#agentic_ai#agents#authentication#bedrock#core#gateway#identity_management#memory_management#production_code#runtime Amazon Bedrock AgentCore lets you build, deploy, and run AI agents securely at scale with any framework like CrewAI or LangGraph and any model, without managing complex infrastructure. It offers serverless runtime for long tasks up to 8 hours, gateway to connect tools like Slack or APIs easily, memory for personalized experiences, identity management, built-in code interpreter and browser tools, plus observability. This saves time by skipping heavy setup, speeds prototypes to production, cuts costs with pay-per-use, and boosts security—helping you create powerful agents faster for real business needs. https://github.com/awslabs/amazon-bedrock-agentcore-samples