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Memvid MCP Server

An Model Context Protocol (MCP) server for Memvid, enabling AI agents to use persistent, file-based memory.

Features

  • Project-based Memory: Create and manage isolated memory files (.mv2) for different projects.

  • Add Content: Store text documents, code snippets, and metadata.

  • Semantic Search: Find relevant content using Memvid's hybrid search (lexical + semantic).

  • Ask Memory (Optional): Ask natural language questions about your stored data (requires OpenAI API Key).

Installation

npm install -g memvid-mcp-server # or bun add -g memvid-mcp-server

Configuration

This server can be used with any MCP-compliant client (e.g., Claude Desktop, Cursor).

Environment Variables

Variable

Description

Required

OPENAI_API_KEY

Your OpenAI API Key. Required to enable the ask_memory tool and for semantic embeddings in some modes.

No (Optional)

MEMVID_LOCAL_STORAGE

Set to "1" to store memory files in ./memvid_mcp (current directory) instead of ~/.memvid_mcp.

No (Optional)

Claude Desktop Configuration

Add the following to your claude_desktop_config.json:

{ "mcpServers": { "memvid": { "command": "npx", "args": ["-y", "memvid-mcp-server@latest"], "env": { "OPENAI_API_KEY": "sk-...", "MEMVID_LOCAL_STORAGE": "0" } } } }

Note: If you do not provide OPENAI_API_KEY, the ask_memory tool will not be available, but you can still use create_or_open_memory, add_content, and search_memory (lexical mode).

Tools

  1. create_or_open_memory: Initialize a new project memory or open an existing one.

  2. add_content: Add text and metadata to the memory.

  3. search_memory: Search your memory. Use query="*" to list all recent items.

  4. ask_memory: (Optional) Ask questions about your memory using an LLM.

Development

# Install dependencies bun install # Run locally bun run src/index.ts # Build bun build ./src/index.ts --compile --outfile server

Credits

This MCP Server is a wrapper around the powerful Memvid SDK. Full credit goes to the Memvid team for their excellent technology.

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