Rememberizer

You can run the Rememberizer MCP Server for Common Knowledge to access and query your private Rememberizer knowledge base. It exposes tools to retrieve semantically similar internal knowledge, perform agented searches, list available knowledge sources, and remember new pieces of information for quick recall. This enables fast context-aware answers and streamlined knowledge retrieval within your project’s MCP workflow.

How to use

You interact with the Rememberizer MCP Server through an MCP client. Start the server using your MCP client’s configuration, then invoke the available tools to search or store knowledge. Typical workflows include: querying for semantically similar internal documents, performing targeted searches across Slack, Google Drive, Gmail, or uploaded files, and saving new facts for future recall. Use the client to run searches with your query text, then read back the matched chunks or summaries. You can also save important notes so they become part of your Rememberizer memory and can be retrieved later by the search tools.

How to install

Prerequisites: make sure you have a compatible environment for running MCP servers and a client capable of connecting to an MCP endpoint. The Rememberizer MCP server is intended to be run in your development or production environment where you can start the local server process and connect via your MCP client.

Install and run the MCP server using the provided stdio command configuration. The server is designed to be started through a local command that the MCP client can invoke.

Additional sections

Configuration notes: You will typically run the server via a local command that the MCP client can execute. The Rememberizer MCP Server for Common Knowledge is designed to integrate with your client by exposing a stdio-based runtime entry. The client configuration example below demonstrates how to wire the server into your MCP client setup.

Security and access: Manage access to your Rememberizer knowledge by controlling who can query or memorize content. Use your standard authentication and authorization practices for your environment and limit memory operations to trusted users or teams.

Examples and tips: When you run queries, tailor your input to the allowed length for the match input (up to a few hundred words) to get precise results. When saving information with remember_this, provide a clear name so you can recall it later using the search tools.

Tools and configuration examples

The server provides these tools to interact with your internal knowledge base:

{
  "mcpServers": {
    "rememberizer": {
      "command": "uvx",
      "args": ["rememberizer-mcp-quanghs-gdrive"]
    }
  }
}

Available tools

retrieve_semantically_similar_internal_knowledge

Takes a text block and returns cosine-similar matches from your Rememberizer knowledge repository. Inputs include match_this (up to 400 words), n_results (optional), from_datetime_ISO8601, and to_datetime_ISO8601. Returns: text output of matching chunks.

smart_search_internal_knowledge

Performs an agentic search across personal/team knowledge sources (Slack, Gmail, Google Drive, Dropbox, uploaded files). Inputs include query (up to 400 words), user_context (optional), n_results (optional), from_datetime_ISO8601, and to_datetime_ISO8601. Returns: text output.

list_internal_knowledge_systems

Lists available internal knowledge sources and integrations (e.g., Slack, Gmail, Google Drive, Dropbox, uploaded files). Returns: list of integrations.

rememberizer_account_information

Retrieves account information for your Rememberizer knowledge repository, including owner name and email.

list_personal_team_knowledge_documents

Fetches a paginated list of documents in your Rememberizer knowledge system. Supports page and page_size for navigation.

remember_this

Saves a piece of text information in Rememberizer for future recall by the search tools. Inputs include name (identifier for the info) and content (information to memorize).