#RPC framework
222 related articles
·2 min
OpenSpiel 2.0 Released: Reinforcement Learning Framework Fully Embraces Large Language Models
OpenSpiel 2.0 by Google DeepMind adds LLM fine-tuning examples, MCP tool server, JSON trajectories, AlphaZero on JAX, 19 new games, and Windows support.
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Protocol Buffers Deep Dive: Principles…
·2 min
Protocol Buffers Deep Dive: Principles, Advantages, and Use Cases
A deep dive into Google's open-source Protocol Buffers (Protobuf): binary encoding, schema definitions, gRPC integration, and real-world microservice use cases.
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·7 min
Claude Code Practical Tutorial: A Complete Beginner's Guide to Automating Your Entire Workflow
No coding required! This guide breaks down the complete Claude workflow: custom Projects, batch SEO content, one-sentence tool building with Artifacts, and Claude Code terminal ops—with real traffic-growth cases.
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·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.
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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.
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·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.
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·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.
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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.
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·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.
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·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.
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·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.
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·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.
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·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.
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·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.
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·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.
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·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.
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·4 min
A Deep Dive into ASP.NET Core: The Complete Guide to Microsoft's Cross-Platform Web Framework
A comprehensive analysis of ASP.NET Core's architecture and technical strengths: cross-platform deployment, high-performance Kestrel server, modular middleware, built-in DI, and modern web capabilities like Blazor, gRPC, and SignalR.
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·3 min
Multiple AI Agents Sharing a Codebase: Parallel Collaboration Conflicts and Practical Solutions
When multiple AI coding agents work on the same codebase simultaneously, how do you avoid interface conflicts and coordination chaos? A deep dive into Git worktree isolation, contract-first design, and intent declaration.
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·5 min
Hands-On with PageAgent: Add AI Agent Capabilities to Web Pages with a Single Line of Code
In-depth hands-on review of Alibaba's open-source web automation tool PageAgent: three integration methods, script execution analysis, and a full breakdown of current limitations. Add AI Agent capabilities to web pages with one line of JS.
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·6 min
Hands-On With Hermes Agent's Eight Major Updates: A Complete Guide to AI Automation and Self-Evolution
The Hermes Agent gets a major upgrade with eight new features: native iMessage, parallel background sub-agents, Unreal Engine MCP support, a self-evolving Skill Hub, and more. A hands-on breakdown of the core changes and their real impact on personal AI automation workflows.
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