claude mcp add mcp-memory-service -- npx -y mcp-memory-service
A pasteable skeleton generated from the repository name. Check the project README for the exact package and arguments.
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2,020 โ ยท doobidoo/mcp-memory-service ยท read from the repository page ยท (checked 2026-10-16 20:00:20)
Source
collected from the punkpeye/awesome-mcp-servers list ยท type: MCP server
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first seen 2026-10-09 ยท last seen 2026-10-16 ยท seen 32ร ยท listed by 7 sources
Score
score 703 ยท 2,020 โ ยท 7 sources ยท mcp
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repository doobidoo/mcp-memory-service๏ผfirst catalogued 2026-10-09๏ผlast seen 2026-10-16ใThere is no official certification or quality rating here โ we record sources and dates only.
Persistent Shared Memory for AI Agent Pipelines Open-source memory backend for AI agents โ **REST API, MCP, OAuth, CLI, dashboard**. One self-hosted service, every transport. Agents store decisions, share causal knowledge graphs, and retrieve context in 5ms โ without cloud lock-in or API costs. **Works with LangGraph ยท CrewAI ยท AutoGen ยท any HTTP client ยท Claude Desktop ยท OpenCode** --- --- โถ The 3D knowledge graph in motion โ every memory a glowing node, every relationship a curved edge. --- Why Agents Need This Your AI assistant forgets everything when you start a new chat. You spend 10 minutes re-explaining your architecture. **Again.** MCP Memory Service captures project context, architecture decisions, and code patterns automatically โ new sessions start with everything already known. | Without mcp-memory-service | With mcp-memory-service | |---|---| | Each agent run starts from zero | Agents retrieve prior decisions in 5ms | | Memory is local to one graph/run | Memory is shared across all agents and runs | | You manage Redis + Pinecone + glue code | One self-hosted service, zero cloud cost | | No causal relationships between facts | Knowledge graph with typed edges (causes, fixes, contradicts) | | Context window limits create amnesia | Autonomous consolidation compresses old memories | **Key capabilities for agent pipelines:** - **Framework-agnostic REST API** โ no MCP client library needed; the live endpoint list is at /api/docs - **Knowledge graph** โ agents share causal chains, not just facts - **X-Agent-ID header** โ auto-tag memories by agent identity for scoped retrieval - **conversation_id** โ bypass deduplication for incremental conversation storage - **SSE events** โ real-time notifications when any agent stores or deletes a memory - **Embeddings run locally via ONNX** โ memory never leaves your infrastructure --- ๐ Get Started in 60 Seconds > Not sure which setup fits? The **Setup Guide** walks you to the right path in under a minute. **1. Install:** **2. Configure your AI client:** Claude Desktop Add to your config file: - **macOS**: ~/Library/Application Support/Claude/claude_desktop_config.json - **Windows**: %APPDATA%\Claude\claude_desktop_config.json - **Linux**: ~/.config/Claude/claude_desktop_config.json Restart Claude Desktop. Your AI now remembers everything across sessions. Claude Code Restart Claude Code. Memory tools will appear automatically. Agent pipelines (REST API โ LangGraph, CrewAI, AutoGen, any HTTP client) Store a memory with POST /api/memories, search with POST /api/search, retrieve by tag with POST /api/search/by-tag. Send X-Agent-ID: on a store request and the server tags the memory agent: , which a tag search then scopes retrieval by. Worked examples per framework, the tag conventions and the async patterns: **docs/agents/** OpenCode The plugin ships as repository files for the local plugin directory, so clone the repository once even if you installed from PyPI. Install steps, the /memory slash command and the endpoint override: **opencode/README.md** claude.ai and ChatGPT (browser โ Remote MCP) Remote MCP puts persistent memory in the browser on any device, no desktop app required: OAuth 2.0 over HTTPS, self-hosted or cloud-hosted. Both claude.ai and ChatGPT (Developer Mode) connect to the same endpoint. Cloudflare Tunnel quick start, Let's Encrypt, nginx, Caddy and Docker production setups: **Remote MCP Setup** ยท 5-minute tutorial Advanced: custom backends and team setup