What dependencies are required?
You need Python with `uvx` installed, and a valid Rememberizer API token set as the `REMEMBERIZER_API_TOKEN` environment variable.
MCP Server Rememberizer
@skydeckai
基本信息
关于 MCP Server Rememberizer
An MCP Server to enable global access to Rememberizer
MCP Server Rememberizer 配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"mcp-server-rememberizer": {
"command": "uvx",
"args": [
"mcp-server-rememberizer"
]
}
}
}MCP Server Rememberizer 工具
12`match_this` (string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledge
Search results as text output
`query` (string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledge
Search results as text output
None required
List of available integrations
None required
Account information details
`page` (integer, optional): Page number for pagination, starts at 1 (default: 1)
List of documents
`name` (string): Name of the information. This is used to identify the information in the future
Confirmation data
概览
What is MCP Server Rememberizer?
MCP Server Rememberizer is a Model Context Protocol server that enables Large Language Models to search, retrieve, and manage documents and integrations through the Rememberizer API. It provides access to personal/team internal knowledge repositories including documents and Slack discussions.
How to use MCP Server Rememberizer?
Install via uvx mcp-server-rememberizer and set the REMEMBERIZER_API_TOKEN environment variable. Configure with Claude Desktop by adding the server entry to claude_desktop_config.json or use the MseeP AI Helper app to install and configure the token.
Key features of MCP Server Rememberizer
- Retrieve semantically similar internal knowledge chunks
- Smart search across multiple document sources
- List integrated knowledge systems (Slack, Gmail, Dropbox, etc.)
- View account holder name and email
- Paginated list of all personal/team documents
- Save text snippets for future retrieval
Use cases of MCP Server Rememberizer
- Search internal Slack discussions, Gmail, or Google Drive documents from an LLM
- Retrieve relevant chunks from a large knowledge base for context-aware responses
- Save meeting notes or important information for later semantic recall
- List and audit all documents in your Rememberizer knowledge repository
- Get account details to verify or debug integration
常见问题
Where is my data stored?
Data is stored in your personal/team Rememberizer knowledge repository, which includes sources like Slack, Gmail, Dropbox, Google Drive, and uploaded files.
Are there usage limits?
Semantic search and retrieval inputs are limited to 400 words. The number of results is optional (e.g., `n_results=3` for up to 5, `n_results=10` for more). Date filters can be applied in ISO 8601 format.
How do I authenticate?
Set the environment variable `REMEMBERIZER_API_TOKEN` with your Rememberizer API key. API keys can be registered in the Rememberizer developer settings.
What transport protocol does it use?
The server implements the Model Context Protocol (MCP) – no additional transport details are provided in the README.
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