#MCP Memory
723 related articles
·3 min
MCP Memory: A Lightweight AI Agent Memory Solution Built with SQLite
Deep dive into the MCP Memory open-source project: how SQLite FTS5 and Google OKF enable persistent AI agent memory without vector databases—zero dependencies, minimal cost.
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Adaptive Recall: A Deep Dive into Pers…
·2 min
Adaptive Recall: A Deep Dive into Persistent Memory for AI Assistants via MCP
Adaptive Recall uses MCP (Model Context Protocol) to give AI assistants like Claude persistent memory across sessions, featuring vector storage, semantic retrieval, and adaptive forgetting.
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·2 min
Three Essential Claude Code Configuration Techniques: A Practical Guide to CLAUDE.md, Memory & MCP
Master three Claude Code configuration techniques: use CLAUDE.md for project rules, Memory for auto-learning preferences, and MCP for connecting GitHub and external tools.
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Tutorials·2 min
Two MCP Plugins Combined: Solving Claude Code's Memory Loss Problem in Large Projects
Claude Code loses memory on large projects? Learn how Cloud Context and Context Mode MCP plugins combine vector-indexed retrieval with 98% compression to solve context window overflow.
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Tutorials·3 min
Gemini CLI Complete Guide: MCP Extensions & Memory Files in Practice
Complete guide to Google Gemini CLI setup, MCP Server extensions, and memory files. Covers 1M token context analysis, Context7 docs, Taskmaster task breakdown, and more.
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Tutorials·3 min
Graphiti MCP Server Configuration Tutorial: Giving Cursor and Claude Code Persistent Memory
Step-by-step guide to configuring Graphiti MCP Server, adding persistent cross-session memory to Cursor and Claude Code via Neo4j temporal knowledge graphs.
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Product Reviews·3 min
MeMo Open-Source AI Agent Platform In-Depth Review: Long-Term Memory + MCP Protocol + Multi-Bot Collaboration in Practice
In-depth review of MeMo, an open-source AI Agent platform. Covers long-term memory, MCP protocol, multi-Bot container isolation, omni-channel deployment, with setup tutorials and usage tips.
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Product Reviews·3 min
Team Memory MCP: A Deep Dive into the Shared Memory System for AI Coding Agents
Deep dive into team-memory-mcp, an open-source shared memory system for AI coding agents like Claude Code and Cursor, featuring Bayesian confidence scoring and temporal decay via MCP protocol.
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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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·3 min
Semantica: A Traceable 'Black Box' for AI Agent Decision-Making
Semantica is an open-source project with 8,600+ GitHub stars that provides decision recording and data provenance for AI Agents. It supports rule validation, knowledge graph visualization, and multi-Agent collaboration.
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·4 min
From Backend to Agent Engineer: What P7 Interviews Really Test
How can a 6-year backend dev transition to AI Agent engineer? Deep dive into P7 interview essentials: validation, semantic cache, state machines, and MCP.
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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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·1 min
screenpipe: 24/7 Screen Recording That Gives AI Agents Long-Term Memory
screenpipe continuously records your screen, audio, and activity to give AI Agents long-term memory. Local-first privacy, MCP protocol support, and cross-platform coverage for Mac, Windows, and Linux.
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·3 min
From Models to MCP: A Complete Guide to the Underlying Logic of AI Tool Calling
Trace the full path from model fundamentals through deployment, Function Calling, to MCP protocol, explaining how MCP standardizes the connection between LLMs and external tools.
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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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·3 min
Local MCP over stdio: An Architecture Seam Design Guide for Agentic Applications
A deep dive into using local MCP over stdio as an architectural seam for agentic applications, covering model-tool decoupling, testability, process management, and comparison with cloud MCP.
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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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·5 min
MCP Protocol Explained: The Path to Standardized Tool Integration for AI Agents
Deep dive into MCP (Model Context Protocol): its core value, three-role architecture, and engineering practices. Includes a FastMCP server tutorial and LangChain integration guide.
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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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·4 min
WorldCloud: An Agentic Framework for Generating Explorable 3D Open Worlds from a Single Sentence
Deep dive into WorldCloud's technical architecture: how multi-agent collaboration generates large-scale, editable, explorable 3D open worlds from a single natural language description.
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