Memflow MCP Server

MemFlow MCP - A Model Context Protocol server for seamless memory management with intelligent search

Local serverstdio

What is the Memflow MCP MCP server?

Memflow MCP becomes available to MCP clients through the memflow mcp mcp server. MemFlow MCP - A Model Context Protocol server for seamless memory management with intelligent search.

What Memflow MCP does

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.

Tools it exposes

Once connected, the assistant can call these 3 tools directly:

  • addMemory — Store content with optional tags
  • searchMemory — Search memories with semantic matching
  • listMemories — Browse stored memories with filtering

Installing the memflow mcp mcp server

The server is distributed via npm as memflow-mcp, so most clients can run it without a manual build step. Add it to your MCP client's configuration and restart the client to pick it up — the copy-paste configs for Claude Desktop, Claude Code and Cursor are on this page.

Configuration

Before the server will start you need to supply 2 environment variables: MEMBANK_API_URL, MEMBANK_API_KEY. Keep credentials in your client's env block or a secrets manager rather than committing them.

Requirements

  • Node.js 18+ - Memory Bank API server running

Where it fits

Knowledge and memory servers address the most frustrating trait of language models — walking into every conversation with no recollection of the last one. Memflow MCP sits in that group, and the shape of its toolset — addMemory, searchMemory, listMemories — tells you what it is really for. Worth comparing against the other knowledge memory servers in this directory before you commit to one, since several overlap in scope but differ sharply in setup cost and permissions.

Practical notes

  • This server runs locally, so it operates with whatever access your machine and its credentials already have. Scope that deliberately rather than by default.
  • It will not start until its required credentials are present, so set those before wondering why the tools never appear.
  • Maintained by sacmii.
  • MCP clients ask for confirmation before each tool call by default. Keep that on while you learn what the memflow mcp mcp server actually does with your data.
  • Every entry in this directory is reviewed by hand before it goes live, and details are checked against the project's own documentation.

Available tools

ToolWhat it does
addMemoryStore content with optional tags
searchMemorySearch memories with semantic matching
listMemoriesBrowse stored memories with filtering

How to install the Memflow MCP MCP server

Then configure Claude Desktop:

```json
{
  "mcpServers": {
    "memflow": {
      "command": "/your/npx/path",
      "args": ["-y", "memflow-mcp"],
      "env": {
        "MEMBANK_API_URL": "http://localhost:3000"
      }
    }
  }
}

Configuration as documented by the project. Restart the client after saving.

Configuration

  • Node.js 18+ - Memory Bank API server running
VariableDescriptionRequired
MEMBANK_API_URLEndpoint or connection string the server talks to.Yes
MEMBANK_API_KEYCredential the server authenticates with.Yes

Example prompts to try

  • Use Memflow MCP to addMemory.
  • Use Memflow MCP to searchMemory.
  • Use Memflow MCP to listMemories.

Frequently asked questions

It connects Memflow MCP to MCP-compatible AI assistants such as Claude and Cursor, exposing 3 tools (addMemory, searchMemory, listMemories) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Memflow MCP directly.