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Rememberizer AI
community
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An MCP server designed for interacting with the Rememberizer data source, facilitating enhanced knowledge retrieval.
MCP Server Rememberizer
A Model Context Protocol server for interacting with Rememberizer's document and knowledge management API. This server enables Large Language Models to search, retrieve, and manage documents and integrations through Rememberizer.
Please note that
mcp-server-rememberizer
is currently in development and the functionality may be subject to change.Components
Resources
The server provides access to two types of resources: Documents or Slack discussions
Tools
-
retrieve_semantically_similar_internal_knowledge
- Send a block of text and retrieve cosine similar matches from your connected Rememberizer personal/team internal knowledge and memory repository
- Input:
(string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledgematch_this
(integer, optional): Number of semantically similar chunks of text to return. Use 'n_results=3' for up to 5, and 'n_results=10' for more informationn_results
(string, optional): Start date in ISO 8601 format with timezone (e.g., 2023-01-01T00:00:00Z). Use this to filter results from a specific datefrom_datetime_ISO8601
(string, optional): End date in ISO 8601 format with timezone (e.g., 2024-01-01T00:00:00Z). Use this to filter results until a specific dateto_datetime_ISO8601
- Returns: Search results as text output
-
smart_search_internal_knowledge
- Search for documents in Rememberizer in its personal/team internal knowledge and memory repository using a simple query that returns the results of an agentic search. The search may include sources such as Slack discussions, Gmail, Dropbox documents, Google Drive documents, and uploaded files
- Input:
(string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledgequery
(string, optional): The additional context for the query. You might need to summarize the conversation up to this point for better context-awared resultsuser_context
(integer, optional): Number of semantically similar chunks of text to return. Use 'n_results=3' for up to 5, and 'n_results=10' for more informationn_results
(string, optional): Start date in ISO 8601 format with timezone (e.g., 2023-01-01T00:00:00Z). Use this to filter results from a specific datefrom_datetime_ISO8601
(string, optional): End date in ISO 8601 format with timezone (e.g., 2024-01-01T00:00:00Z). Use this to filter results until a specific dateto_datetime_ISO8601
- Returns: Search results as text output
-
list_internal_knowledge_systems
- List the sources of personal/team internal knowledge. These may include Slack discussions, Gmail, Dropbox documents, Google Drive documents, and uploaded files
- Input: None required
- Returns: List of available integrations
-
rememberizer_account_information
- Get information about your Rememberizer.ai personal/team knowledge repository account. This includes account holder name and email address
- Input: None required
- Returns: Account information details
-
list_personal_team_knowledge_documents
- Retrieves a paginated list of all documents in your personal/team knowledge system. Sources could include Slack discussions, Gmail, Dropbox documents, Google Drive documents, and uploaded files
- Input:
(integer, optional): Page number for pagination, starts at 1 (default: 1)page
(integer, optional): Number of documents per page, range 1-1000 (default: 100)page_size
- Returns: List of documents
-
remember_this
- Save a piece of text information in your Rememberizer.ai knowledge system so that it may be recalled in future through tools retrieve_semantically_similar_internal_knowledge or smart_search_internal_knowledge
- Input:
(string): Name of the information. This is used to identify the information in the futurename
(string): The information you wish to memorizecontent
- Returns: Confirmation data
Installation
Via mcp-get.com
npx @michaellatman/mcp-get@latest install mcp-server-rememberizer
Via Smithery
npx -y @smithery/cli install mcp-server-rememberizer --client claude
Via SkyDeck AI Helper App
If you have SkyDeck AI Helper app installed, you can search for "Rememberizer" and install the mcp-server-rememberizer.

Configuration
Environment Variables
The following environment variables are required:
: Your Rememberizer API tokenREMEMBERIZER_API_TOKEN
You can register an API key by creating your own Common Knowledge in Rememberizer.
Usage with Claude Desktop
Add this to your
claude_desktop_config.json
:"mcpServers": { "rememberizer": { "command": "uvx", "args": ["mcp-server-rememberizer"], "env": { "REMEMBERIZER_API_TOKEN": "your_rememberizer_api_token" } }, }
Usage with SkyDeck AI Helper App
Add the env REMEMBERIZER_API_TOKEN to mcp-server-rememberizer.

With support from the Rememberizer MCP server, you can now ask the following questions in your Claude Desktop app or SkyDeck AI GenStudio
-
What is my Rememberizer account?
-
List all documents that I have there.
-
Give me a quick summary about "..."
-
and so on...
License
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
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