#client-server architecture
477 related articles
Deep Dives·2 min
MCP Protocol Architecture Deep Dive: Host-Client-Server Three-Layer Design and Three Core Primitives
Deep dive into MCP's Host-Client-Server three-layer architecture and its Resources, Tools, Prompts primitives. Learn how it transforms AI tool integration from M×N to M+N.
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·3 min
Vercel Open-Sources fx: A 6MB Zig-Powered Coding Agent Where Minimalist Design Makes Models Stronger
Vercel open-sources fx, a 6MB Zig-powered coding agent with near-instant startup. Supports local/cloud models, MCP protocol, and embeddable design.
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·2 min
Anagnorisis: An Open-Source Local Recommendation Engine That Puts You Back in Control of the Algorithm
Anagnorisis is an open-source local recommendation engine that returns algorithmic control from cloud vendors to users, enabling privacy-first, portable, and auditable personalized recommendations.
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·3 min
Vessel: A Local LLM Observability Proxy for Request Capture and Cross-Model Replay Comparison
Vessel is a free, open-source local LLM observability proxy supporting Ollama, LM Studio, and more. Capture requests, track tokens, replay across models, with built-in MCP server and Web UI.
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·2 min
The MCP Server Ecosystem at a Glance: The AI Integration Revolution Behind 90K Stars
Explore the awesome-mcp-servers project with 90K+ stars: how this MCP server directory drives standardized AI integration across databases, dev tools, cloud platforms, and more.
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·3 min
MCP Server Language Selection Guide: How to Choose Between Rust, Go, TypeScript, Python, and Java
Compare Rust, Go, TypeScript, Python, and Java for MCP Server development across deployment complexity, ecosystem maturity, and user-friendliness with scenario-based selection guidance.
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·5 min
AI Agent Skill Stack Fully Decoded: Building Professional Agents with 16 Pluggable Skills
Deep dive into 16 practical AI Agent Skills covering code review, evals, frontend design, communication, memory, and automation — revealing the modular methodology behind Agent engineering.
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·3 min
LangChain Beginner's Guide: A Three-Layer Learning Method to Take You from Understanding to Mastery
A systematic introduction to LangChain's core role in the LLM tech stack, plus a proven three-layer learning method—Understand, Code, Explain—to help developers master LLM, Agent, and MCP development.
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·3 min
Cloak Fingerprint Browser + MCP: Letting AI Automate the Entire Reverse Engineering and Packet Capture Workflow
How Cloak's source-code-level fingerprint browser and 69 MCP tools let AI automate the full reverse engineering workflow—from bypassing CAPTCHAs to packet capture.
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·3 min
One Decorator to Solve the Duplicate Tool Execution Problem in AI Agents
The idempotent-tools Python library prevents duplicate tool execution in AI Agents with a single @idempotent decorator, supporting SQLite, Redis, LangGraph, and CrewAI.
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·2 min
Kitbitz: 2000+ Free Hand-Drawn Assets with CC0 License for Commercial Use
Kitbitz offers 2000+ free hand-drawn assets under CC0 license, with SVG/PNG downloads and deep Figma integration across 13 themed kits for games, apps, and maps.
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·4 min
Transitioning to AI Agent Development: A Complete Three-Stage Learning Path for Programmers
Why do programmers keep failing at AI Agent development? This guide breaks down a 3-stage learning path: ReAct & Tool Calling fundamentals, LangChain engineering, and production-grade project delivery.
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·3 min
AiCode Hands-On Review: A Complete Guide to the Open-Source AI Coding Tool for Android
Hands-on review of AiCode, an open-source Android AI coding tool covering API provider setup, container environments, MCP protocol, Token cost tracking, and Git management.
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·3 min
MCP-Builder.ai: A Managed Platform for Building AI Data Connectors in Minutes Using Natural Language
MCP-Builder.ai lets developers build, host, and secure MCP Servers using natural language, connecting databases, APIs, and apps to Claude, ChatGPT, and Cursor in minutes.
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·2 min
Qencode MCP: Using Natural Language to Drive AI-Powered Video Transcoding and Processing
Qencode MCP integrates cloud video processing into the AI Agent ecosystem via Model Context Protocol, enabling natural language-driven video transcoding, analysis, editing, optimization, and delivery.
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·6 min
Flask Creator's Conversation: Why We Need to Slow Down in the AI Coding Era
Flask creator Armin Ronacher and minimalist Agent Pi's author Mario Zechner discuss AI coding limitations, code quality decline, MCP vs CLI, and why engineers need to slow down.
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·4 min
AI Large Language Models + MCP Protocol: A Hands-On Tutorial for Fully Automated Unity Digital Twin Construction
Learn how AI LLMs paired with MCP servers can fully automate Unity digital twin construction without manual operations. Covers MCP setup, Claude Code integration, and auto-generated conveyor scenes.
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·3 min
Buddy Visual Tests: AI-Powered Visual Regression Testing Tool That Automatically Reviews UI Changes Before Merge
Buddy Visual Tests embeds visual regression testing into CI/CD, using pixel-by-pixel comparison to catch UI changes. With MCP support, AI Agents can automatically discover, fix, and close visual bugs before merge.
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·3 min
ComfyUI MCP Open-Sourced: Build AI Image Generation Workflows with Natural Language
ComfyUI officially open-sources Comfy MCP, letting users build AI image generation workflows with natural language via the MCP protocol. Full deployment guide and demo review included.
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·2 min
Semantica: The Open-Source Reasoning Engine That Creates Complete Evidence Chains for AI Decisions
Semantica is an open-source deterministic reasoning engine that builds complete evidence chains for AI decisions using knowledge graphs and W3C PROV standards, with 6000x query acceleration and self-hosted deployment for regulated industries.
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