
Room MCP Server
The Room MCP Server enables AI assistants to collaborate in virtual rooms via the Room protocol, supporting multi-agent workflows, invitation management, transc...
FlowHunt provides an additional security layer between your internal systems and AI tools, giving you granular control over which tools are accessible from your MCP servers. MCP servers hosted in our infrastructure can be seamlessly integrated with FlowHunt's chatbot as well as popular AI platforms like ChatGPT, Claude, and various AI editors.
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.
No specific prompt templates are mentioned in the repository or documentation.
No explicit resource definitions are detailed in the repository or documentation.
No Windsurf-specific instructions provided in the repository.
git clone https://github.com/liveblocks/liveblocks-mcp-server.git
npm install
npm run build
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..."
}
}
}
}
git clone https://github.com/liveblocks/liveblocks-mcp-server.git
npm install
npm run build
{
"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..."
}
}
}
}
No Cline-specific instructions provided in the repository.
LIVEBLOCKS_SECRET_KEY in the env block of the configuration JSON as shown above.{
"env": {
"LIVEBLOCKS_SECRET_KEY": "sk_dev_Ns35f5G..."
},
"inputs": { }
}
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.
| Section | Availability | Details/Notes |
|---|---|---|
| Overview | ✅ | Overview available from README and project description. |
| List of Prompts | ⛔ | No prompt templates mentioned in the repo. |
| List of Resources | ⛔ | No resource definitions found in the repo. |
| List of Tools | ✅ | High-level tool descriptions inferred from README; no detailed tool API listed. |
| Securing API Keys | ✅ | Clearly described in setup instructions. |
| Sampling Support (less important in evaluation) | ⛔ | Not mentioned anywhere in the repo or docs. |
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.
| Has a LICENSE | ✅ (Apache-2.0) |
|---|---|
| Has at least one tool | ✅ |
| Number of Forks | 3 |
| Number of Stars | 4 |
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.
Empower your AI agents to manage collaborative workspaces, threads, comments, notifications, and more with Liveblocks MCP Server. Automate and streamline teamwork in real time.

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