#JSON-RPC
223 related articles
·3 min
LangChain V1.3 in Practice: Mastering AI Engineering Mindset — From Tool User to Tool Master
Why do AI results vary so dramatically? LangChain V1.3 reveals the answer: engineering mindset. Covers LangGraph, Deep Agent, RAG, Time Travel, and more.
Read more →
Fuse: An Open-Source MCP Tool Built to…
·2 min
Fuse: An Open-Source MCP Tool Built to Optimize Claude Code for C# Codebases
Fuse is an open-source MCP/CLI tool that improves Claude Code's performance on large C# codebases using Roslyn-powered semantic queries to reduce token usage.
Read more →
Code Review Graph: Using Intelligent C…
·3 min
Code Review Graph: Using Intelligent Code Graphs to Deliver Precise Context for AI
Code Review Graph is a local-first open-source code intelligence graph supporting MCP and CLI. It reduces AI context noise in large repos with persistent graph structures.
Read more →
·3 min
AI Coding Agents Explosion: CodeWell Goes Open Source, Kimi K3 Launches, Claude Gets Browser Access
CodeWell open-sources a multi-model terminal coding agent, Kimi K3 launches with ultra-long context, MiniMax Code 2.0 rebuilds its Agent architecture, and Claude gets browser access. AI is accelerating from content generation to task execution.
Read more →
·3 min
Build an MCP Server in 10 Minutes: Let AI Call Your Code Directly
MCP (Model Context Protocol) is the open standard for AI tool integration. Build your own MCP server with ~20 lines of Python. Learn tools, resources, prompts, and both local and remote deployment.
Read more →
Designing APIs for AI Agents: A Paradi…
·3 min
Designing APIs for AI Agents: A Paradigm Shift from Human Interfaces to Agent-Friendly Design
When AI Agents become the primary API callers, traditional interface design assumptions break down. This article explores agent-friendly API design principles and how MCP is driving this paradigm shift.
Read more →
·3 min
Cherry Studio + MCP: A Practical Guide to Building AI Agents with Local Deployment
Learn how to build an automated AI agent using Cherry Studio, MCP protocol, and locally deployed models — covering DeepSeek integration, web scraping, and private knowledge base setup.
Read more →
·2 min
The Four Core Concepts of AI Agents Explained: Function Calling, Tool, MCP, and Skill
A clear breakdown of the four core AI Agent concepts: Function Calling, Tool, MCP, and Skill — understand the full tech stack behind intelligent agent development.
Read more →
·3 min
Adversarial Testing of AI Agents in the Terminal via MCP
Learn how to use MCP (Model Context Protocol) to run adversarial tests on AI agents in the terminal, covering prompt injection, privilege escalation, and dangerous command execution scenarios.
Read more →
·3 min
Dify + MCP in Practice: Building a Multi-Scene Life Assistant Agent with ModelScope MCP Marketplace
Build a multi-scene life assistant Agent using ModelScope MCP Marketplace and Dify. Integrates Amap, LeetCode, recipe, and news MCP Servers with Qwen3 via Chatflow.
Read more →
·4 min
From Tokens to Agents: A Complete Guide to Core AI Concepts
Master 8 core AI concepts — LLM, Token, Context Window, Prompt, Tool, Agent, MCP, and Agent Skill — and understand the complete logic chain behind AI's evolution.
Read more →
·2 min
Zero Prompts! Turn Your Design Mockup into a Promo Video with One Skill
LibTV's 'Screenshot to Promo Video' Skill lets designers generate promo videos by simply uploading a mockup — no prompts, no MCP setup required.
Read more →
·2 min
MCP vs. Skills: A Clear Breakdown of AI Agent Architecture Layers
MCP and Skills aren't alternatives — they occupy different layers of AI Agent architecture. This article breaks down Function Call, MCP, and Skills to clarify each layer's role.
Read more →
·2 min
Deep Dive into MCP: How Large Language Models Connect to the Outside World
MCP (Model Context Protocol) is the standardized protocol connecting AI models to external tools and data — the 'USB-C port' of the AI era. Learn its origins and value.
Read more →
Adaptive Recall: A Deep Dive into Pers…
·2 min
Adaptive Recall: A Deep Dive into Persistent Memory for AI Assistants via MCP
Adaptive Recall uses MCP (Model Context Protocol) to give AI assistants like Claude persistent memory across sessions, featuring vector storage, semantic retrieval, and adaptive forgetting.
Read more →
·5 min
The Definitive Guide to Claude Code: Core Methodology and Best Practices for Agentic Programming
A deep dive into Claude Code, the definitive course from DeepLearning.AI and Anthropic: from agentic principles and context optimization to three hands-on cases—RAG chatbot, Figma-to-frontend, and data analysis. Master AI-assisted coding methodology.
Read more →
·3 min
Getting Started with Codex: A Comprehensive Comparison with Claude Code and How to Choose
A deep comparison of Codex vs. Claude Code on pricing, stability, and frontend/backend strengths — plus how to choose between Cursor, Claude Code, and Codex.
Read more →
·4 min
MCP Protocol Deep Dive: Its Relationship with Function Calling and Agents, Plus a Practical Guide
Deep dive into MCP (Model Context Protocol): clarifying the three-layer relationship between MCP, Function Calling, and Agents, covering protocol roles, call flows, transport choices, and production security for AI developers.
Read more →
·5 min
Open-Source MCP Server: Automatically Verifying the Authenticity of AI-Generated Paper Citations
AI "citation hallucination" threatens academic integrity—LLMs generate perfectly formatted but nonexistent references. This open-source MCP server verifies AI citations in real time against CrossRef, PubMed, and more, catching fakes at the source.
Read more →
·4 min
Zhipu GLM-5.2 Released: China's First Open-Source Model to Cross the 'Primary Model' Threshold
Zhipu releases GLM-5.2 with 1M token context, matching GPT-5.x and Claude. Zcode 3.0 offers 3M free daily calls with one-click migration from Claude Code and Codex.
Read more →