Rememberizer MCP Server

What does “Rememberizer” MCP Server do?

The Rememberizer MCP Server is an implementation of the Model Context Protocol (MCP) that acts as a bridge between AI assistants and Rememberizer’s document and knowledge management API. By enabling seamless access to personal and team knowledge repositories, this server empowers language models to search, retrieve, and manage a wide range of documents and integrations such as Slack discussions, Gmail, Dropbox, Google Drive, and uploaded files. Its primary role is to facilitate enhanced development workflows by supporting complex queries, semantic search, and knowledge discovery, all from within an AI-driven environment. This enables developers and teams to efficiently surface relevant information, automate knowledge management, and integrate contextual data into their AI-powered processes.

List of Prompts

No explicit prompt templates are mentioned in the repository.

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List of Resources

• Documents: Access and retrieve information from uploaded documents stored in Rememberizer’s internal knowledge repository.
• Slack Discussions: Search and extract relevant information from integrated Slack conversations.
• (Potentially includes Gmail, Dropbox, and Google Drive documents as sources, as referenced in tools, but not explicitly listed as top-level resources.)

List of Tools

• retrieve_semantically_similar_internal_knowledge
  • Sends a block of text and retrieves cosine-similar matches from your connected Rememberizer knowledge repository, filtered by optional date ranges and result limits.
• smart_search_internal_knowledge
  • Performs an agentic search in Rememberizer’s knowledge repository using a simple query, including context from various sources (Slack, Gmail, Dropbox, Google Drive, uploaded files).
• list_internal_knowledge_systems
  • Lists all sources of your internal knowledge, such as Slack, Gmail, Dropbox, Google Drive, and uploaded files.
• rememberizer_account_information
  • Retrieves account information about your Rememberizer personal or team knowledge repository, including account holder details.

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Use Cases of this MCP Server

• Semantic Knowledge Retrieval
  • Enables developers and AI agents to find contextually similar information from a large corpus of documents and discussions, dramatically improving research and problem-solving efficiency.
• Unified Search Across Integrations
  • Aggregates and searches knowledge from diverse platforms (Slack, Gmail, Dropbox, Google Drive), providing a single interface for comprehensive information discovery.
• Team Knowledge Management
  • Facilitates team-wide access to shared documents and discussions, supporting onboarding, collaboration, and institutional memory.
• Automated Documentation and Insights
  • AI assistants can auto-generate summaries, reports, or answer questions by leveraging the organization’s entire knowledge base, streamlining workflows.
• Account and Integration Overview
  • Provides visibility into connected knowledge sources and account information, aiding in system administration and integration management.

How to set it up

Windsurf

1. Ensure you have Node.js and Windsurf installed.
2. Open your Windsurf configuration file (e.g., windsurf.json).
3. Add the Rememberizer MCP Server with the following JSON snippet:

   "mcpServers": {
     "rememberizer": {
       "command": "npx",
       "args": ["@rememberizer/mcp-server@latest"]
     }
   }
   

4. Save your configuration and restart Windsurf.
5. Verify the server is running via the Windsurf dashboard.

Securing API Keys

Store sensitive API keys in environment variables. Example:

"mcpServers": {
  "rememberizer": {
    "command": "npx",
    "args": ["@rememberizer/mcp-server@latest"],
    "env": {
      "REMEMBERIZER_API_KEY": "${REMEMBERIZER_API_KEY_FROM_ENV}"
    },
    "inputs": {
      "api_key": "${REMEMBERIZER_API_KEY_FROM_ENV}"
    }
  }
}

Claude

1. Confirm Claude supports external MCP servers.
2. Locate the Claude MCP integration settings file.
3. Add the server configuration:

   "mcpServers": {
     "rememberizer": {
       "command": "npx",
       "args": ["@rememberizer/mcp-server@latest"]
     }
   }
   

4. Save the changes and restart Claude.
5. Check the integration status in Claude’s settings.

Securing API Keys

"env": {
  "REMEMBERIZER_API_KEY": "${REMEMBERIZER_API_KEY_FROM_ENV}"
},
"inputs": {
  "api_key": "${REMEMBERIZER_API_KEY_FROM_ENV}"
}

Cursor

1. Make sure Node.js is installed and Cursor supports MCP plugins.
2. Find the relevant Cursor configuration file.
3. Insert Rememberizer MCP as below:

   "mcpServers": {
     "rememberizer": {
       "command": "npx",
       "args": ["@rememberizer/mcp-server@latest"]
     }
   }
   

4. Save the config and restart Cursor.
5. Confirm Rememberizer appears in the Cursor MCP panel.

Securing API Keys

"env": {
  "REMEMBERIZER_API_KEY": "${REMEMBERIZER_API_KEY_FROM_ENV}"
},
"inputs": {
  "api_key": "${REMEMBERIZER_API_KEY_FROM_ENV}"
}

Cline

1. Install Node.js and ensure Cline supports MCP servers.
2. Edit your Cline MCP server configuration.
3. Add Rememberizer MCP:

   "mcpServers": {
     "rememberizer": {
       "command": "npx",
       "args": ["@rememberizer/mcp-server@latest"]
     }
   }
   

4. Save and restart Cline.
5. Validate the connection in the Cline dashboard.

Securing API Keys

"env": {
  "REMEMBERIZER_API_KEY": "${REMEMBERIZER_API_KEY_FROM_ENV}"
},
"inputs": {
  "api_key": "${REMEMBERIZER_API_KEY_FROM_ENV}"
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "rememberizer": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “rememberizer” to the actual name of your MCP server and replace the URL with your own MCP server URL.

Overview

| Roots Support | ⛔ | Not mentioned |

Our opinion

The Rememberizer MCP Server offers robust document and knowledge management integration for AI workflows, with clearly documented tools and resource support. The lack of prompt templates and sampling/roots support is a minor drawback but overall, it provides a valuable and practical MCP server, especially for knowledge-driven teams.

Rating: 8/10

MCP Score