#JSON-RPC
288 related articles
Product Reviews·3 min
OpenCode: A Deep Dive into the Terminal AI Coding Tool Built with Go
Deep dive into OpenCode, a terminal AI coding tool built with Go. Blazing-fast startup, multi-model support (Gemini, Claude), built-in Vim editor, and LSP integration. Compared with Claude Code and Aider.
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Tutorials·2 min
Why Qwen3 Is the Best Open-Source Model for MCP Agent Development
Analysis of Qwen3's advantages for MCP agent development, comparing DeepSeek R1's lack of Function Calling, covering MoE architecture and thinking mode switching.
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Tutorials·3 min
Cursor AI + Back4App Full-Stack Development in Practice: Build Production-Ready Web Apps with a Single Prompt
Learn how to use Cursor AI with Back4App to auto-build user auth, databases, and deploy a full finance tracker app using natural language — no backend code needed.
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Deep Dives·4 min
MCP Apps Deep Dive: AI Tools Move from Text Exchange to Interactive Collaboration
Deep analysis of MCP Apps: how Anthropic and OpenAI's official MCP extension enables AI tools to return interactive UIs, solving the context gap with Human-in-the-Loop collaboration.
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Product Reviews·2 min
Fitten Code MCP Launch: Connecting AI Agents to Unlimited External Tools
Fitten Code Agent now supports MCP protocol, enabling flexible integration with GitHub, Bing search, Excel, and other external tools to become a super AI programming assistant.
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Deep Dives·2 min
ACP Protocol Explained: A New Open-Source Protocol Standardizing Communication Between IDEs and Coding Agents
Deep dive into ACP (Agent-Client Protocol): how Zed and Google Gemini standardize IDE-to-coding-agent communication, its architecture, and how it complements MCP.
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Product Reviews·3 min
Context Mode: How One MCP Plugin Cured AI Coding Assistants' Amnesia
Context Mode solves AI coding assistants' context amnesia via sandbox isolation, session continuity tracking, and code-thinking philosophy—compressing context consumption by 99% and earning 9,700 Stars in two months.
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Tutorials·3 min
LangGraph Multi-Agent Architecture: Graph Structure Principles and Enterprise-Level Implementation Guide
Deep dive into LangGraph's core graph structure design, single and multi-agent collaboration patterns, MCP protocol integration, and Time Travel fault-tolerance, with enterprise-level hybrid multi-agent architecture implementation.
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Tutorials·3 min
LangGraph Multi-Agent Architecture: Core Principles and Enterprise-Level Implementation Guide
Deep dive into LangGraph multi-agent architecture covering Graph structure principles, MCP service integration, Time Travel debugging, and supervised multi-agent enterprise implementation patterns.
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Deep Dives·3 min
Deep Dive into MCP Code Execution & Agent Skills: Compressing 150K Tokens Down to 2,000
Deep analysis of two MCP ecosystem breakthroughs: code execution compresses tool definitions from 150K to 2K tokens, and Agent Skills enable capability packaging and reuse.
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Deep Dives·2 min
MCP Protocol Explained: The USB-C of the AI World
Deep dive into MCP (Model Context Protocol): architecture, how it works, and security risks. Learn the key differences between MCP and Function Calling.
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Tutorials·3 min
MCP Protocol Explained: The New Agent Communication Standard Replacing Function Calling
Deep dive into MCP (Model Context Protocol): its core concepts, three communication mechanisms, and ecosystem. Learn how MCP replaces Function Calling with Streamable HTTP and SDK 2.0.
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Tutorials·3 min
Open-Source Multi-Agent Intelligent Diagnostic System: Deep Dive into MCP + RAG + Skill Routing Architecture
Deep dive into an open-source multi-Agent diagnostic system built on modified OneCall, featuring MCP real-time interaction, RAG-enhanced Q&A, and Skill routing to minimize Token consumption.
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Deep Dives·2 min
What Is the MCP Protocol? Understanding the USB-C of the AI World
MCP (Model Context Protocol) is a unified standard for connecting AI models to external tools. This guide explains MCP's core concepts, practical value, and provides a quick-start tutorial.
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Tutorials·2 min
The Six Key AI Agent Protocols Explained: MCP, A2A, UCP, AP2, A2UI, and AGUI
Deep dive into six core AI agent protocols: MCP, A2A, UCP, AP2, A2UI, and AGUI — covering tool integration, multi-agent collaboration, commerce, payments, and dynamic UI, with Google ADK examples.
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Tutorials·2 min
8 Core Concepts of AI Programming: From Chat Mode to Engineering Mode
A systematic breakdown of 8 core AI programming concepts: Agent, Sandbox, Permissions, Cloud.md, MCP, Skills, Subagents, and Non-interactive — evolving from chat mode to engineering mode.
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Tutorials·3 min
Figma MCP in Practice: Complete Tutorial for Connecting Design Files Directly to an AI Code Editor
Step-by-step tutorial on connecting Figma design files to the Antigravity AI code editor via Figma MCP, covering MCP setup, Access Token config, and verification.
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Tutorials·2 min
MCP Protocol Beginner's Guide: AI Model Context Protocol Architecture & Practical Integration
A detailed guide to MCP (Model Context Protocol) covering its three-layer architecture, ecosystem marketplace, and practical integration for connecting AI models with external tools.
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Tutorials·2 min
TRAE Editor + Figma MCP Hands-On Tutorial: Convert Design Files to Web Code in One Click
Step-by-step tutorial: Install TRAE editor, configure Figma MCP, and auto-generate HTML web code from Figma designs with OpenRouter API setup included.
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Tutorials·2 min
Claude Code + Figma MCP in Practice: Bidirectional Sync Between Web Generation and Design Files
Step-by-step guide to configuring Claude Code with Figma MCP for bidirectional sync between AI-generated web pages and Figma design files, including setup and deployment.
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