Rememberizer MCP Server
Enables semantic search and retrieval of information from Dropbox documents stored in the Rememberizer knowledge repository.
Enables semantic search and retrieval of information from Gmail messages stored in the Rememberizer knowledge repository.
Enables semantic search and retrieval of information from Google Drive documents stored in the Rememberizer knowledge repository.
Enables semantic search and retrieval of information from Slack discussions stored in the Rememberizer knowledge repository.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Rememberizer MCP Serverfind similar discussions about our Q4 marketing strategy"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Rememberizer MCP Server for Common Knowledge
This is my test CK
Please note that rememberizer-mcp-test-ck 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_knowledgeSend a block of text and retrieve cosine similar matches from your connected Rememberizer personal/team internal knowledge and memory repository
Input:
match_this(string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledgen_results(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 informationfrom_datetime_ISO8601(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 dateto_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 date
Returns: Search results as text output
smart_search_internal_knowledgeSearch 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:
query(string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledgeuser_context(string, optional): The additional context for the query. You might need to summarize the conversation up to this point for better context-awared resultsn_results(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 informationfrom_datetime_ISO8601(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 dateto_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 date
Returns: Search results as text output
list_internal_knowledge_systemsList 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_informationGet 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_documentsRetrieves 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:
page(integer, optional): Page number for pagination, starts at 1 (default: 1)page_size(integer, optional): Number of documents per page, range 1-1000 (default: 100)
Returns: List of documents
remember_thisSave 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:
name(string): Name of the information. This is used to identify the information in the futurecontent(string): The information you wish to memorize
Returns: Confirmation data
Related MCP server: Rememberizer MCP Server for Common Knowledge
Installation
Via SkyDeck AI Helper App
If you have SkyDeck AI Helper app installed, you can search for "Rememberizer" and install the rememberizer-mcp-test-ck.

Configuration
Usage with Claude Desktop
Add this to your claude_desktop_config.json:
"mcpServers": {
"rememberizer": {
"command": "uvx",
"args": ["rememberizer-mcp-test-ck"]
},
}Usage with SkyDeck AI Helper App
With support from the Rememberizer MCP server for Common Knowledge, you can now ask the following questions in your Claude Desktop app or SkyDeck AI GenStudio
What is this Common Knowledge?
List all documents that it has 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.
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- Alicense-qualityDmaintenanceProvides access to personal/team knowledge repositories with tools to search, retrieve, and save information from various sources including Slack, Gmail, and document storage platforms.Last updatedApache 2.0
- Alicense-qualityDmaintenanceEnables accessing and managing personal/team internal knowledge repository with tools for semantic search, smart search, document listing, and saving information for future recall.Last updatedApache 2.0
- Alicense-qualityDmaintenanceEnables semantic search and retrieval of information from personal and team knowledge repositories including Slack, Gmail, Dropbox, Google Drive, and uploaded files. Allows storing new information for future recall through AI-powered search.Last updatedApache 2.0
- Alicense-qualityDmaintenanceProvides a persistent, vendor-neutral memory layer that allows AI tools and agents to share context and knowledge across different platforms while maintaining local data ownership. It enables users to store, recall, and manage structured memories through hybrid semantic search and automated context assembly.Last updated24Apache 2.0
Related MCP Connectors
Universal memory for AI agents and tools. Save, organize and search context anywhere.
Search everything you save: YouTube, articles, podcasts, PDFs, Notion, Obsidian. API key or OAuth.
Your company's brain for AI agents. Cited, permission-aware knowledge across every system.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/skydeckai/rememberizer-mcp-test-ck'
If you have feedback or need assistance with the MCP directory API, please join our Discord server