Enables Large Language Models to store and retrieve persistent memories with intelligent search capabilities.
A Model Context Protocol (MCP) server that enables Large Language Models to store and retrieve persistent memories with intelligent search capabilities.
MemFlow MCP provides seamless integration between LLMs like Claude and your Memory Bank API, allowing for persistent memory management across conversations. The server supports adding memories with tags, semantic search, and flexible memory retrieval.
npx memflow-mcp
Or install globally:
pnpm add -g memflow-mcp
MEMBANK_API_URL=http://localhost:3000
MEMBANK_API_KEY=your-api-key # optional
See CLAUDE_DESKTOP_CONFIG.md for detailed configuration options for different Node.js installations.
Quick start - Find your npx path and use it:
which npx
Then configure Claude Desktop:
{
"mcpServers": {
"memflow": {
"command": "/your/npx/path",
"args": ["-y", "memflow-mcp"],
"env": {
"MEMBANK_API_URL": "http://localhost:3000"
}
}
}
}
Once configured, you can use these commands in Claude:
Add this to memory: "Claude can now remember things across conversations"
Search my memories for "conversations"
List my recent memories
Find your npx path:
which npx
Use this full path in your Claude Desktop config.
Common paths:
/Users/username/.asdf/shims/npx
/usr/local/bin/npx
/opt/homebrew/bin/npx
/usr/bin/npx
Test it works:
/your/npx/path -y memflow-mcp
MEMBANK_API_URL
is set correctlyYour Memory Bank API should support:
POST /memory
- Create memoryGET /memory
- List/search memoriesMIT
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