MCP-Flomo-Server: Integrated AI Application for Seamless Content Recording

Overview: What is MCP-Flomo-Server?

MCP-Flomo-Server is an advanced server application designed to facilitate the integration of Model Context Protocol (MCP) with Flomo, a powerful note-taking application. By leveraging MCP, this server enables AI applications such as Claude Desktop, Continue, Cursor, and more to directly interact with Flomo’s APIs, thereby streamlining the process of recording valuable information during conversations with AI assistants.

🔧 Core Features & MCP Capabilities

MCP-Flomo-Server is built on top of MCP, a protocol that standardizes interactions between AI applications and external tools. This ensures compatibility across different AI clients while providing a robust framework for data exchange and manipulation. The key features include:

• Tool Interface: Provides an MCP tool interface that allows AI applications to seamlessly invoke the Flomo API.
• Content Delivery: Seamlessly sends content from AI dialogues to the user's Flomo account via the Flomo API.
• Customization: Utilizes environment variables for configuration, allowing users and developers to tailor the server’s behavior according to their needs.
• Type Safety: Developed using TypeScript, ensuring type safety and robustness in handling data.

⚙️ MCP Architecture & Protocol Implementation

MCP-Flomo-Server operates on a clear structure that enables smooth interactions between AI applications and external tools. Its architecture revolves around the following components:

1. Protocol Layer: Implements the MCP protocol to handle communication between the server and various AI clients.
2. Tool Adapter: Acts as an adapter layer between the MCP protocol and Flomo’s API, facilitating data exchange.
3. Configuration Layer: Manages environment variables that configure the behavior of the server.

The diagram below illustrates the flow of interactions:

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

🚀 Getting Started with Installation

Premises & Prerequisites

To begin using MCP-Flomo-Server, ensure you meet the following requirements:

• Node.js (v16 or higher): To run and build the application.
• npm/yarn: For dependency management.
• Flomo API Key: Obtainable from Flomo's web interface.

Installation Steps

Follow these steps to install and configure MCP-Flomo-Server:

1. Clone the Repository:

   git clone https://github.com/codeugar/mcp-flomo-server.git
   cd mcp-flomo-server
   

2. Install Dependencies:

   npm install
   

3. Configure Flomo API: Modify src/index.ts to set your Flomo API key:

   let flomo_api = "YOUR_FLOMO_API_KEY"
   

💡 Key Use Cases in AI Workflows

Real-World AI Workflow Scenario 1: Note Recording During Conversations

Imagine an interaction where a user is conversing with their AI assistant (e.g., Claude Desktop). The user can instruct the AI to record important information directly into Flomo. Here’s how it works:

1. AI Assistant Interaction: User asks the AI to "Record this point in Flomo."
2. MCP Integration: The AI, via MCP, sends a request to the MCP-Flomo-Server.
3. Data Processing: The server processes the request and sends data through the Flomo API.
4. Note Creation: Information is stored in the user's Flomo account.

Real-World AI Workflow Scenario 2: Streamlining Knowledge Management

Incorporate MCP-Flomo-Server into an extensive workflow of knowledge management:

1. Initial Setup: Install and configure the server as described above.
2. Integrating with AI Assistant: Ensure all AI clients are using MCP to connect to Flomo.
3. Continuous Recording: As the user engages in discussions or receives information through their AI assistant, this information is automatically recorded into Flomo.

🔌 Integration with MCP Clients

MCP-Flomo-Server supports multiple MCP clients for seamless integration:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

📊 Performance & Compatibility Matrix

Ensure that MCP-Flomo-Server performs optimally and can handle a wide range of AI clients. The compatibility matrix is as follows:

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

🛠️ Advanced Configuration & Security

Configuration Code Sample

// src/index.ts
let flomo_api = process.env.FLOMO_API || 'default_value'

Environment Variables for Security

Ensure the application utilizes environment variables to store sensitive information, such as API keys and other credentials.

❓ Frequently Asked Questions (FAQ)

1. Q: How do I get my Flomo API key? A: Log in to your Flomo account on their web interface and navigate to settings to create a new API key.

2. Q: Why is there no console output when starting the server? A: The server was designed to be silent during normal operation, focusing solely on processing MCP client requests.

3. Q: How can I verify that my Flomo recording works properly? A: Trigger a few recording commands through your AI assistant and check your Flomo account for new notes.

4. Q: Can I use this server with other AI assistants besides the ones listed? A: Yes, as long as they support MCP.

5. Q: Is there any way to customize how notes are recorded in Flomo? A: Yes, via environment variables and custom scripts within src/index.ts.

👨‍💻 Development & Contribution Guidelines

Contributions to this project are welcomed! Submit issues or pull requests for enhancement.

🌐 MCP Ecosystem & Resources

For further exploration of the MCP ecosystem, visit official documents and resources on the Model Context Protocol website.