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Rememb MCP Server

@LuizEduPP

代码仓库

基本信息

分类

开发工具

许可证

MIT

传输方式

stdio

作者

LuizEduPP

提交者

Luiz Eduardo

关于 Rememb MCP Server

Persistent memory for AI agents — local, portable, zero config. Works with Cursor, Windsurf, Claude via MCP.

Rememb MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "rememb": {
      "command": "rememb",
      "args": [
        "mcp"
      ]
    }
  }
}

Rememb MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Rememb?

Rememb is a local-first persistent memory layer for AI agents. It provides structured entries, keyword search, versioning, diff, restore, and an audit trail — all without requiring a cloud service or API keys. It is designed for teams and solo developers who operate agents across sessions and need to avoid context loss.

How to use Rememb?

Install with pip install rememb. The recommended integration is via MCP: add a rememb server entry to your IDE's MCP config using the command rememb mcp. Restart the IDE and the agent can read, write, search, and restore memory automatically. For a persistent local process, start with rememb mcp --transport sse --host 127.0.0.1 --port 8765. You can also run the web UI with rememb to inspect and configure memory.

Key features of Rememb

  • Local-first memory with JSON or SQLite storage on disk
  • Structured entries with customizable sections and tags
  • Keyword and token search for efficient recall
  • Non-destructive versioning with diff and restore
  • Soft delete and duplicate consolidation
  • 60 bundled agent skills accessible via web UI and MCP
  • MCP integration (stdio and SSE) for IDE and client use
  • Web UI for supervision, statistics, and settings

Use cases of Rememb

  • Resume an agent session with full context from prior work
  • Maintain an auditable trail of decisions made by AI agents
  • Reduce re-explaining project facts (tech stack, architecture) each session
  • Quickly search for specific context without rereading entire chat history
  • Store user preferences and recurring requests for consistent agent behavior

常见问题

1

What makes Rememb different from cloud-based memory services?

Rememb is local-first: it stores memory as plain JSON or SQLite on disk, with no servers, API keys, or accounts. You keep full control and can copy the store anywhere.

2

What are the runtime dependencies?

Rememb requires Python 3.10 to 3.12. No additional embedding models or external services are needed at runtime.

3

Where does Rememb store data?

Data is stored locally in the `~/.rememb/` directory by default. You can copy this folder to move the memory store to another machine.

4

Which transports does Rememb support for MCP?

Rememb supports stdio (default for IDE integration) and SSE for a persistent local process. The SSE mode must be started separately with the `--transport sse` flag.

5

Does Rememb require authentication?

No. Rememb operates entirely locally and does not use any authentication or API keys. Access is limited to the local machine.

评论

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