Metadata-Version: 2.4
Name: mcp-server-rememberizer
Version: 0.1.6
Summary: 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.
Author-email: Rememberizer <support@rememberizer.ai>
License-File: LICENSE
Requires-Python: >=3.11
Requires-Dist: httpx>=0.27.2
Requires-Dist: mcp>=1.0.0
Requires-Dist: python-dotenv>=1.0.1
Description-Content-Type: text/markdown

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# MCP Server Rememberizer

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A [Model Context Protocol](https://www.anthropic.com/news/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

1. `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:
        - `match_this` (string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledge
        - `n_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 information
        - `from_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 date
        - `to_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

2. `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:
        - `query` (string): Up to a 400-word sentence for which you wish to find semantically similar chunks of knowledge
        - `user_context` (string, optional): The additional context for the query. You might need to summarize the conversation up to this point for better context-awared results
        - `n_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 information
        - `from_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 date
        - `to_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

3. `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

4. `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

5. `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:
        - `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

6. `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:
        - `name` (string): Name of the information. This is used to identify the information in the future
        - `content` (string): The information you wish to memorize
    - Returns: Confirmation data

## Installation

### Manual Installation

```bash
uvx mcp-server-rememberizer
```

### Via MseeP AI Helper App

If you have MseeP AI Helper app installed, you can search for "Rememberizer" and install the mcp-server-rememberizer.

![MseeP AI Helper](https://www.gitbook.com/cdn-cgi/image/dpr=2,width=760,onerror=redirect,format=auto/https%3A%2F%2Ffiles.gitbook.com%2Fv0%2Fb%2Fgitbook-x-prod.appspot.com%2Fo%2Fspaces%252FyNqpTh7Mh66N0RnO0k24%252Fuploads%252FuTpQuJffWohPRTvjmyVe%252FScreenshot%25202025-07-29%2520at%252014.43.12.png%3Falt%3Dmedia%26token%3D7f046f3b-dc69-4f09-8f8c-978097f0066e)

## Configuration

### Environment Variables

The following environment variables are required:

-   `REMEMBERIZER_API_TOKEN`: Your Rememberizer API token

You can register an API key by creating your own [Common Knowledge in Rememberizer](https://docs.rememberizer.ai/developer/registering-and-using-api-keys).

### Usage with Claude Desktop

Add this to your `claude_desktop_config.json`:

```json
"mcpServers": {
  "rememberizer": {
      "command": "uvx",
      "args": ["mcp-server-rememberizer"],
      "env": {
        "REMEMBERIZER_API_TOKEN": "your_rememberizer_api_token"
      }
    },
}
```

### Usage with MseeP AI Helper App

Add the env REMEMBERIZER_API_TOKEN to mcp-server-rememberizer.

![MseeP AI Helper Configuration](https://www.gitbook.com/cdn-cgi/image/dpr=2,width=760,onerror=redirect,format=auto/https%3A%2F%2Ffiles.gitbook.com%2Fv0%2Fb%2Fgitbook-x-prod.appspot.com%2Fo%2Fspaces%252FyNqpTh7Mh66N0RnO0k24%252Fuploads%252FHxisSUT1anmCpoHhW8CJ%252FScreenshot%25202025-07-29%2520at%252014.45.42.png%3Falt%3Dmedia%26token%3D1332394a-cdbe-4e7b-9099-1dbf14e58ffb)

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...

To learn more about Rememberizer MCP Server: https://docs.rememberizer.ai/personal-use/integrations/rememberizer-mcp-servers

## License

This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
