liveblocks/liveblocks-mcp-server
by Various
MCP server for Liveblocks.
MCP
liveblocks/liveblocks-mcp-server
Added 1 June 2026
Overview
An MCP server that connects AI agents to Liveblocks, enabling them to interact with real-time collaboration data. It uses the Model Context Protocol to expose Liveblocks APIs for reading and writing storage, presence, and other primitives.
Best for
Best for
Developers adding AI copilot functionality to applications using Liveblocks for real-time collaboration
Use cases
- Enable AI assistants to read and update Liveblocks storage in real-time apps
- Allow AI agents to manage user presence and broadcast events
- Build copilot features that automate Liveblocks room operations
Notes
An MCP server that connects AI agents to Liveblocks, enabling them to interact with real-time collaboration data. It uses the Model Context Protocol to expose Liveblocks APIs for reading and writing storage, presence, and other primitives.
16 stars on GitHub. Last updated 2026-05-11. Licensed Apache-2.0.
Use cases
- Enable AI assistants to read and update Liveblocks storage in real-time apps
- Allow AI agents to manage user presence and broadcast events
- Build copilot features that automate Liveblocks room operations
Pros
- Open source and written in TypeScript, easy to integrate with Node.js projects
- Leverages the standard MCP protocol for interoperability with AI clients
- Directly targets Liveblocks, reducing boilerplate for agentic workflows
Cons
- Low star count suggests limited community adoption and testing
- Sparse documentation beyond the basic description
- Requires an MCP-compatible client, adding a dependency for AI integrations
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Open source and written in TypeScript, easy to integrate with Node.js projects
- Leverages the standard MCP protocol for interoperability with AI clients
- Directly targets Liveblocks, reducing boilerplate for agentic workflows
Cons
- Low star count suggests limited community adoption and testing
- Sparse documentation beyond the basic description
- Requires an MCP-compatible client, adding a dependency for AI integrations
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