#MCP persistent memory
150 related articles
·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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·3 min
Building a Local AI Coding Agent on Mac: A Complete Guide with Ollama, OpenCode, and MCP
A complete guide to building a local AI coding agent on a 32GB Mac: Ollama for local inference, OpenCode as the agent framework, and MCP memory servers for cross-session context. Code stays on-device, no subscription fees.
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·7 min
OpenClaw vs Hermes: An In-Depth Comparison and Selection Guide for AI Agent Tools
An in-depth comparison of OpenClaw and Hermes Agent, covering skill management, memory mechanisms, security, and gateway configuration to help you find the right AI agent solution.
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·5 min
ECC: An Agent Enhancement Framework for AI Coding Assistants — Five Core Capabilities Explained
ECC is an agent optimization framework for AI coding assistants like Claude Code, Cursor, and Codex, enhancing them with skills, memory, security, and research-first development capabilities.
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·4 min
Tencent Open-Sources Agent Memory: A Fully Local AI Long-Term Memory Solution with Zero External Dependencies
Tencent Cloud open-sources TencentDB Agent Memory — a fully local AI Agent memory system with a 4-tier progressive pipeline, zero external API dependencies, and 8,100+ GitHub Stars. Ideal for finance, healthcare, and privacy-sensitive use cases.
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·7 min
Getting Started with AI Agents: A Deep Dive into the Perception-Decision-Action Loop
A clear, in-depth guide to how AI Agents work: the paradigm shift from traditional programs, the perception-decision-action loop, and the four pillars—LLMs, tool calling, memory, and RAG.
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·5 min
From Prompts to Harness Engineering: The Evolution of AI Agent Development Paradigms
Why has AI engineering methodology evolved from prompts to context engineering and now Harness engineering? This article examines three paradigms, key bottlenecks, and the Agent = Model + Harness formula.
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·7 min
ManagedAgents.sh: A Deep Dive into the Model-Agnostic Open-Source Managed Agent Platform
ManagedAgents.sh is a model-agnostic managed agent platform from OpenComputer, supporting Claude, Pi, and Codex runtimes with Slack and GitHub integration.
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·7 min
Getting Started with LangChain 1.3: Core Concepts of LLMs and Agents
An in-depth breakdown of LangChain 1.3's core concepts, covering the three major limitations of LLMs, Agent architecture, memory management, and a complete learning path. Master LangChain and LangGraph to quickly build AI development skills.
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·4 min
Harness Engineering: The Third Phase of AI Coding and a Practical Guide to agents.md
A deep dive into Harness Engineering — the third phase of AI coding. Based on research across 2,853 GitHub repos, explore agents.md, Skills, MCP, and eight configuration mechanisms to control your AI coding assistant.
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·7 min
Zero-Basis Learning Path for AI Agents: A Three-Stage Journey from Beginner to Deployment
A systematic zero-basis learning path for AI Agent development, covering Python and LLM fundamentals, five core capabilities like task planning and RAG, and LangChain hands-on practice.
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·6 min
LangChain 1.3 in Practice: A Complete Guide to DeepAgent Architecture and the Harness Philosophy
An in-depth look at LangChain 1.3's core modules and DeepAgent architecture—covering the Harness philosophy, LangGraph internals, HITL, memory management, and guardrails to master production-grade AI Agent development.
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·7 min
Electron + LangGraph in Practice: Building an AI Agent Visual Orchestration App from Scratch
A hands-on guide to building an enterprise-grade AI Agent workflow orchestration app with Electron Forge and LangGraph, covering local LLM deployment (Qwen3-0.6B), node-based visual canvas design, and full Function Calling integration.
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·7 min
Building AI Agent Frameworks with TypeScript: The Core Development Paradigm for Full-Stack Developers
An in-depth look at why TypeScript is the top choice for AI Agent development: covering Zod structured output validation, LangGraph's graph state machine design, and a full learning path for front-end devs transitioning to full-stack AI.
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·2 min
Chrome DevTools MCP: Giving AI Coding Assistants True Browser Vision
Google Chrome's official chrome-devtools-mcp uses MCP to expose DevTools capabilities to AI coding assistants like Claude and Cursor, enabling screenshots, console reading, and network analysis.
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·7 min
Kontext: One-Click AI Conversation Context Migration, Breaking Down Multi-Model Switching Barriers
Kontext is a context migration tool for multi-AI users, enabling one-click transfer of full conversation history between ChatGPT, Claude, and Gemini to solve the context silo problem.
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·3 min
Three Fatal Flaws of AI Script Writing — and How MCP Services Fix Them
AI script development plagued by amnesia, blindness, and repeat errors? This article examines how MCP service tools — history nodes, node preprocessing, and an error library — systematically fix AI programming's structural flaws.
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·7 min
Harness Engineering: Core Methodology and Practical Guide for Enterprise-Level AI Programming
Can AI really replace programmers? This article explains Harness Engineering principles and its three evolutionary stages, revealing real pain points of enterprise AI programming.
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·6 min
LangChain + MCP in Practice: A Pitfall-Avoidance Guide to LLM Selection and Local Deployment
DeepSeek R1 lacks Function Calling and JSON Output by default. Qwen3's programmable thinking modes make it the top open-source agent choice. Key LLM selection pitfalls and MCP protocol updates.
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·2 min
Files as Memory: How to Finally Cure AI Coding Agents of Context Amnesia
AI coding agents suffering from context amnesia? The planning-with-files project uses Markdown file persistence to enable cross-session task continuity, compatible with 60+ tools including Claude Code and Cursor. 24K+ Stars.
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