Liveblocks MCP Server Integration

What does “Liveblocks” MCP Server do?

The Liveblocks MCP Server acts as a bridge between AI assistants and the Liveblocks real-time collaboration platform. By exposing key functions from the Liveblocks REST API, this server enables AI agents to create, modify, and manage collaborative resources like rooms, threads, comments, notifications, and more. Additionally, it provides read access to advanced features such as Storage and Yjs, facilitating seamless integration for AI-driven workflows. The server empowers developers to automate and streamline collaborative operations, enhancing productivity and enabling intelligent agents to interact with Liveblocks data and collaboration primitives programmatically.

List of Prompts

No specific prompt templates are mentioned in the repository or documentation.

List of Resources

No explicit resource definitions are detailed in the repository or documentation.

List of Tools

• Room Management: Enables creation, modification, and deletion of Liveblocks rooms.
• Thread Management: Allows managing threads within rooms for structured discussions.
• Comment Management: Supports adding, editing, and deleting comments within threads.
• Notification Handling: Provides tools to manage notifications within the Liveblocks ecosystem.
• Storage and Yjs Read Access: Allows AI to read from Liveblocks’ Storage and Yjs for collaborative state management.

Use Cases of this MCP Server

• Collaborative Workspace Automation: AI agents can create and organize rooms, threads, and comments, streamlining collaborative workflows for teams.
• Automated Moderation: Use automated tools to manage and moderate threads and comments, ensuring discussions remain productive and on-topic.
• Notification Management: AI can monitor and manage notifications, alerting users to important changes or updates in real time.
• Integrating Liveblocks with Other Tools: AI can act as a bridge, syncing data between Liveblocks and other platforms or services.
• Real-time Data Access and Reporting: AI assistants can pull and analyze real-time collaborative data from Storage and Yjs, providing insights and summaries to users.

How to set it up

Windsurf

No Windsurf-specific instructions provided in the repository.

Claude

1. Clone the Liveblocks MCP Server repository:

   git clone https://github.com/liveblocks/liveblocks-mcp-server.git
   

2. Build the project:

   npm install
   npm run build
   

3. Get your Liveblocks secret key from the dashboard.
4. Go to File → Settings → Developer → Edit Config in Claude Desktop.
5. Edit claude_desktop_config.json and add:

   {
     "mcpServers": {
       "liveblocks-mcp-server": {
         "command": "node",
         "args": ["/full/path/to/the/repo/liveblocks-mcp-server/build/index.js"],
         "env": {
           "LIVEBLOCKS_SECRET_KEY": "sk_dev_Ns35f5G..."
         }
       }
     }
   }
   

6. Save and ensure the server is enabled.

Cursor

1. Clone the repository:

   git clone https://github.com/liveblocks/liveblocks-mcp-server.git
   

2. Build the project:

   npm install
   npm run build
   

3. Get your Liveblocks secret key from the dashboard.
4. Go to File → Cursor Settings → MCP → Add new server.
5. Add:

   {
     "mcpServers": {
       "liveblocks-mcp-server": {
         "command": "node",
         "args": ["/full/path/to/the/repo/liveblocks-mcp-server/build/index.js"],
         "env": {
           "LIVEBLOCKS_SECRET_KEY": "sk_dev_Ns35f5G..."
         }
       }
     }
   }
   

6. Check it’s enabled in the MCP menu.

Cline

No Cline-specific instructions provided in the repository.

Securing API Keys

• Place your LIVEBLOCKS_SECRET_KEY in the env block of the configuration JSON as shown above.
• Example:

  {
    "env": {
      "LIVEBLOCKS_SECRET_KEY": "sk_dev_Ns35f5G..."
    },
    "inputs": { }
  }
  

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:

{
  "liveblocks-mcp-server": {
    "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 “liveblocks-mcp-server” to the actual name of your MCP server and replace the URL with your own MCP server URL.

Overview

Based on the available documentation and code, the Liveblocks MCP Server provides good setup instructions and offers several collaboration tools, but lacks explicit prompt templates, resource definitions, and details about sampling or roots support. It scores as a practical integration MCP—suitable for Liveblocks users but not as feature-rich for advanced MCP protocol usage.

MCP Score

Overall Rating:
I would rate this MCP server a 6/10. While it is functional and has clear setup instructions, it lacks explicit prompt/resource definitions and advanced MCP features like roots and sampling. It’s strong for Liveblocks integration but limited in broader MCP protocol coverage.