#MCP client
775 related articles
·3 min
OpenAI Codex IDE Extension in Practice: A Complete Guide to VS Code Installation and Local Development
A hands-on guide to installing and configuring the OpenAI Codex IDE extension, covering its three working modes and Agent demo. Supports VS Code, Cursor, and Windsurf.
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·3 min
Claude Code Enterprise Guide: Environment Setup, Git Workflows, and Switching to Chinese AI Models
Enterprise guide to Claude Code: CLI setup, switching to DeepSeek and other Chinese AI models, Git workflow automation, and bug fix loops to boost team productivity.
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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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·3 min
What Is Claude Code? A Five-Dimension Breakdown of AI Coding Assistants
Claude Code isn't just a chat AI — it reads your project files, edits code, and runs commands directly. See how it compares to ChatGPT and Cursor across 5 key dimensions.
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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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·3 min
The Complete Guide to Looping Engineering: Building Efficient Agent Loops from Scratch
A deep dive into Looping Engineering — covering the five core loop elements (Trigger, Goal, Judgment, Feedback, Memory), when to use loops, and a step-by-step guide to building a topic-selection loop with Claude Code.
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·3 min
Cherry Studio + MCP + Ollama: The Complete Guide to Building a Local AI Agent and Private Knowledge Base
A hands-on guide to building a local AI agent and private knowledge base using Cherry Studio, MCP, and Ollama — with web scraping, report generation, and terminal control.
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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
From RAG to Agent: A Complete Architecture Guide for AI-Native Systems
A comprehensive guide to modern AI-native system architecture: LLM reasoning, three RAG paradigms (vector/knowledge graph/BM25), Agents, MCP tool calling, AI gateways, and observability for enterprise AI.
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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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·2 min
AI Truly "Gets Its Hands On" Your Phone: Android Remote Control MCP v1.9.0 Deep Dive
Android Remote Control MCP v1.9.0 adds ChatGPT support, OAuth 2.1 auth, and major WebView reliability fixes. Let AI Agents operate any phone app like a human.
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Smart Proxy: The Key Architecture for …
·3 min
Smart Proxy: The Key Architecture for Running AI Coding Agents Safely and Autonomously
Too much AI permission is risky; too little kills productivity. A smart proxy acts as a controllable middleware layer — intercepting, auditing, and policy-gating AI agent actions in tools like Claude Code and Cursor for safe autonomous operation.
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·2 min
Spring AI in Action: A Complete Guide to LLM Integration for Java Developers
Spring AI is Java's answer to LangChain — offering unified multi-model APIs, structured output, RAG, Tool Calling, and MCP protocol support for enterprise LLM development.
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·3 min
Privacy Risks in Claude Code? Use Docker Sandboxes to Fully Isolate Your AI Coding Tools
Claude Code found to contain user monitoring logic, raising AI tool privacy concerns. Learn how to isolate Claude Code, Codex & Copilot with Docker Sandboxes — full setup and escape testing included.
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·3 min
The Complete OpenAI Codex Practical Guide: From Installation to Enterprise Deployment
A complete guide to OpenAI Codex: CLI setup, slash commands, AGENTS.md, MCP integration, multi-agent collaboration, and a RAG customer service project walkthrough.
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·2 min
Getting Started with Claude Code: How AI Coding Assistants Went from Chatting to Actually Getting Things Done
What is Claude Code? This guide covers 5 core differences from ordinary AI chat tools, including context reading, code execution, MCP tool calls, and a Cursor comparison.
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·3 min
LangChain4j Getting Started Guide: A Java Engineer's Fast Track to AI Application Development
LangChain4j is the AI application development framework built for Java engineers. Integrate DeepSeek, Qwen, and more into Spring Boot — no Python required.
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·3 min
AI Tool Selection Guide for Test Engineers: A Hybrid Approach to Avoid Three Common Pitfalls
How should test engineers choose AI tools? This guide breaks down the pitfalls of pure AI solutions and recommends a hybrid strategy using tools like DeepSeek, TRAE, Claude Code, and Skill encapsulation.
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