How do I install the memos api mcp server?

Use a recorded configuration for your client, replace example credential values and paths, and verify the documented runtime. Restart or reconnect the client, then inspect the available tools.

What credentials does it need?

It reads `MEMOS_API_KEY`, `MEMOS_USER_ID`, `MEMOS_CHANNEL` from the environment. Store these in your client's env block or a secrets manager — never commit them to a repository — and grant the narrowest scope that still covers your use case.

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Memos Api MCP Server

A Model Context Protocol (MCP) implementation for the [MemOS](https://github.com/MemTensor/MemOS) API service. This package provides a command-line

Local serverstdioTypeScript

What is the Memos Api MCP Server?

A Model Context Protocol (MCP) implementation for the MemOS API service. This package provides a command-line interface to

The short version

MCP-compliant API interface
Command-line tool for easy interaction
Built with TypeScript for type safety
Express.js server implementation
Zod schema validation

What it needs from you

Node.js >= 18 - npm or pnpm (recommended)

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.

Recorded tools

Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.

Tool	What it does
messages	Array of messages containing role and content information.
role	Role of the message sender (user or assistant).
content	Message content.
chat_time	(Optional) Message timestamp.
filter	(Optional) Filter conditions, used to precisely limit the memory scope before retrieval.
knowledgebase_ids	(Optional) Array specifying the knowledge bases to search.
include_preference	(Optional) Enable preference memory recall. Default: true.
preference_limit_number	(Optional) Max preference memories to return. Default: 9, max 25.
include_tool_memory	(Optional) Enable tool memory recall. Default: false.
tool_memory_limit_number	(Optional) Max tool memories to return. Default: 6, max 25.
include_skill	(Optional) Enable Skill recall. Default: false.
skill_limit_number	(Optional) Max Skills to return. Default: 6, max 25.
relativity	(Optional) Relevance threshold (0-1) for recalled memories. A value of 0 disables relevance filtering.

How to install the Memos Api MCP Server

{
  "mcpServers": {
    "memos-api-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@memtensor/memos-api-mcp"
      ],
      "env": {
        "MEMOS_API_KEY": "YOUR_MEMOS_API_KEY",
        "MEMOS_USER_ID": "your-user-id",
        "MEMOS_CHANNEL": "the-site-where-you-are-seeing-this-document"
      }
    }
  }
}

From the project documentation. Replace placeholders and example paths before connecting.

Configuration

Node.js >= 18 - npm or pnpm (recommended)

Variable	Description	Required
MEMOS_API_KEY	Declared in the maintainer’s client configuration.	Check documentation
MEMOS_USER_ID	Declared in the maintainer’s client configuration.	Check documentation
MEMOS_CHANNEL	Declared in the maintainer’s client configuration.	Check documentation

Example prompts to try

“Use Memos Api MCP to Parameters.”
“Use Memos Api MCP to messages.”
“Use Memos Api MCP to role.”

Frequently asked questions

A Model Context Protocol (MCP) implementation for the [MemOS](https://github.com/MemTensor/MemOS) API service. This package provides a command-line interface to Confirm the tools offered by your installed version in the connected client. Tool availability and permissions depend on the server and account configuration.

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