#MCP client
747 related articles
·4 min
Spring AI 2.0: Five Key Updates Explained — Marching Toward the Age of AI Agents
Spring AI 2.0 brings five core updates: mandatory upgrade to Spring Boot 4, Tools parsing moving up, a built-in Agentic mechanism, MCP switching to Streamable HTTP, and an on-demand tool Advisor.
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·4 min
Spring AI 2.0 Explained: Five Key Updates Ushering in the Age of AI Agents
Spring AI 2.0 brings five core updates: mandatory Spring Boot 4 upgrade, Tools parsing moved up, built-in Agentic mechanism, MCP switch to Streamable HTTP, and on-demand tool-loading Advisor.
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·4 min
Spring AI 2.0: Five Key Updates Explained — Stepping into the Agent Era
Spring AI 2.0 brings five core updates: mandatory upgrade to Spring Boot 4, lifted Tools parsing, built-in Agentic mechanism, MCP switch to Streamable HTTP, and an on-demand tool-loading Advisor.
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·3 min
Rocky: An Open-Source Coding Agent with Minimal Architecture and Native DeepSeek Integration
Rocky is a minimal, transparent open-source coding agent with a core loop under a few hundred lines of Python, native DeepSeek search, Research mode, and built-in SWE benchmarking for reproducible agent experiments.
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·3 min
Pinterest Medic: Engineering an AI Agent for Automated Spark Failure Diagnosis
How Pinterest engineers built Medic for Apache Spark — a multi-agent auto-diagnosis tool — covering the evolution from a single ReAct agent, observability, log denoising, and end-to-end testing.
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·8 min
The Complete Guide to Agent Testing: Five Core Dimensions and Automation in Practice
An in-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing methods and the transition path for test engineers.
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·8 min
A Complete Guide to Agent Testing: Five Core Dimensions and Automation in Practice
In-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing and the transition path for test engineers.
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·6 min
Hands-On with Panel AI On-Premises Deployment: One-Click Enterprise Adoption and Unified Compute Cluster Scheduling
In-depth review of Panel AI v1.1.1: second-level installation, no-public-IP networking, batch compute cluster management. Learn how enterprise AI on-premises deployment barriers are dramatically lowered.
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·7 min
Getting Started with Claude Code: Five Dimensions That Show Why It Outperforms Ordinary AI
Claude Code isn't just a chat AI—it can directly read projects, modify code, and run commands. This article compares Claude Code with ordinary AI across five dimensions: interaction, context, execution, memory, and tool calling.
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·7 min
Getting Started with Claude Code: Five Dimensions to Understand Why It Outperforms Regular AI
Claude Code isn't just a chat AI—it can directly read projects, modify code, and run commands. This article compares Claude Code with regular AI across five dimensions to help you decide if it's worth trying.
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·4 min
Spring AI 1.0 Practical Guide: A Java Developer's Fast Track to Building AI Applications
Spring AI 1.0 is here — Java developers can now build AI apps without switching to Python. This guide covers LLM integration, RAG, intelligent customer service, and Agent patterns for enterprise deployment.
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·8 min
LangChain Crash Course: A Complete Roadmap from Zero to Agent Development
A systematic roadmap from LangChain and LangGraph to multi-agent development, covering RAG, Tool Calling, MCP, and more, helping developers break into AI app development.
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The Rise of Claude Skills Ecosystem: A…
·2 min
The Rise of Claude Skills Ecosystem: A Modular New Paradigm for Custom AI Workflows
Explore the Claude Skills ecosystem: from prompt engineering to modular skills, covering skill libraries, MCP integrations, and dev frameworks. The awesome-claude-skills list has 68K+ Stars.
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·3 min
AI-Assisted GeeTest Four-Image CAPTCHA Reverse Engineering: A Complete Efficiency Guide
A complete walkthrough of AI-assisted GeeTest four-image CAPTCHA reverse engineering: from capturing the w parameter to AI analyzing obfuscated code and generating runnable scripts in minutes.
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·2 min
MCP for Beginners: The Essential Protocol for AI Agent Development
Learn what MCP (Model Context Protocol) is, why it's replacing Function Calling, and how it breaks AI data silos to enable remote tool invocation for agents.
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·3 min
AI Agent Development Landscape: From Architecture Design to Production Deployment
A systematic overview of the AI Agent tech stack: RAG retrieval, Agent planning, MCP protocol, AI Gateway, and observability — helping developers build production-grade AI systems.
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TradingView MCP: Auto-Analyze Trading …
·2 min
TradingView MCP: Auto-Analyze Trading Charts with Claude AI
tradingview-mcp is an open-source MCP Server connecting Claude AI with TradingView desktop to read charts, identify patterns, and interpret indicators via natural language. 4,500+ stars.
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·3 min
AI Development for Java Engineers: A Complete Guide to LangChain4j Agents
Java developers can build AI apps too! Learn LangChain4j fundamentals including RAG, Agents, Function Calling, and hands-on projects — no Python required.
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·5 min
The Complete Claude Code Guide: Installation, Core Features, and Advanced Workflows
An in-depth guide to Anthropic's Claude Code agentic coding tool, covering installation, pricing plans, model selection, token management, CLAUDE.md global memory, MCP integration, Subagents, and more.
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·5 min
Advanced Claude Code in Practice: Building a Top-Tier AI Development Workflow
In-depth analysis of Claude Code customization methodology: from access, knowledge injection to tooling. Master context window management, zero-overhead Hooks, and MCP & Skills plugin primitives to build a scalable AI software engineering workflow.
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