Give MCP agents local shared memory with MARM

Give MCP agents local shared memory with MARM

Use MARM Memory to give Claude Code, Cursor, Codex, Gemini, and other MCP clients a local-first shared memory server with sessions, semantic recall, notebooks, summaries, and code graph context.

Prerequisites

MARM MCP server, Python or Docker runtime, SQLite-backed local storage, MCP-compatible clients such as Claude Code, Cursor, Codex, Gemini, Qwen, or VS Code agents

Installation

Use the upstream install or setup path that matches your environment:

• npx degit Lyellr88/marm-memory/skills
• pip install marm-mcp-server
• Docker uses the same unified image and key:
• docker run -d --name marm-mcp-server \

Requirements and caveats from upstream:

• | Deployment layer | Pip, Docker, STDIO, HTTP, --swarm, --swarm-max, and --trusted | Lets you run private local memory or shared multi-agent memory with the same MCP surface |

Basic usage or getting-started notes:

• Quick Start

• "server_url": "https://your-marm-domain.example.com/mcp",

• MARM handles lifecycle work internally. Docs and session state initialize on the first real tool call, and packaged docs are indexed into the marm_system memory namespace with source-file hash tracking, so your agent...

• Source: https://github.com/Lyellr88/marm-memory

• Extracted from upstream docs: https://raw.githubusercontent.com/Lyellr88/marm-memory/HEAD/README.md

Documentation

• https://github.com/Lyellr88/marm-memory

Source

• Agent Skill Exchange