The Devs
@thedevs · Post #1159 · 06/29/2018, 06:52 PM
A plain English introduction to JSON web tokens (JWT): what it is and what it isn’t. #article#jwt#security#coding#js @thedevs https://kutt.it/ibVW1N
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Source channel @githubtrending · Post #15409 · Jan 12
#javascript#agentic_ai#agentic_engineering#agentic_framework#agentic_rag#agentic_workflow#ai_assistant#ai_tools#anthropic_claude#autonomous_agents#claude_code#codex#huggingface#jules#mcp_server#model_context_protocol#multi_agent#multi_agent_systems#npx#swarm#swarm_intelligence Claude-Flow v2.7 is an enterprise AI platform with hive-mind swarms, 25 natural language skills, 100+ tools, and AgentDB integration for 96x-164x faster semantic search and 4-32x less memory use. Install via `npx claude-flow@alpha init` after Claude Code, then use commands like `swarm "build API"` for quick tasks or hive-mind for projects. It boosts your coding speed with 84.8% problem-solving rate, automation, GitHub tools, and persistent memory—saving you hours on complex development. https://github.com/ruvnet/claude-flow
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djangoproject
@djangoproject · Post #389 · 07/21/2017, 03:12 PM
https://thinkster.io/topics/django Looking to build #fullstack apps with #Django? Looking to build a production ready Django #JSON#API? Building a Production Ready Django JSON API 🔸Setting up #JWT Authentication 🔸Profiles 🔸Articles 🔸Comments 🔸Following 🔸Favoriting 🔸Tagging 🔸Pagination 🔸Filtering 🔸Conclusion Configuring Django Settings for Production Building #Web#Applications with Django and #AngularJS 🔸Learning Django and AngularJS 🔸Setting up your environment 🔸Extending Django's built-in User model 🔸Serializing the Account Model 🔸Registering new users 🔸Logging users in 🔸Logging users out 🔸Making a Post model 🔸Rendering Post objects 🔸Making new posts 🔸Displaying user profiles 🔸Updating user profiles 🔸Congratulations, you did it!
GitHub Trends
@githubtrending · Post #15066 · 08/16/2025, 12:30 PM
#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