Compatible with every major AI agent and IDE
What is the Liveblocks MCP Server?
Connect your Liveblocks account to any AI agent to orchestrate multiplayer experiences and real-time collaboration features through natural language.
What you can do
- Room Management — List, create, update, and delete rooms to manage your application's collaborative spaces.
- User Authentication — Generate access tokens and identify users with specific permissions using
authorize_userandidentify_user. - Collaborative Storage — Inspect and patch room storage state or manage Yjs documents for shared editing.
- Comments & Threads — Query, create, and resolve comment threads to keep track of team discussions within rooms.
- Real-time Presence — List active users in a room or broadcast custom events to connected clients.
How it works
- Subscribe to this server
- Enter your Liveblocks Secret Key
- Start managing your real-time infrastructure from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Full-stack Developers — quickly debug room storage, manage user permissions, or clear stale rooms without leaving the terminal or IDE.
- Product Managers — monitor active collaboration sessions and review comment threads across different project rooms.
- DevOps Engineers — automate the provisioning of collaborative environments and manage access rules programmatically.
Built-in capabilities (18)
Obtain an access token for a client to enter a room
Broadcast a JSON event to a room
Create a new room
Create a thread and the first comment
Delete a room
Retrieve room details
Get the room's Storage tree
Get a specific thread
Get a JSON representation of the Yjs document
Permissions are managed on the backend. Obtain an ID token for a client
Initialize or reinitialize Storage
List users currently in the room
Can be filtered by metadata or access. List rooms with filtering and pagination
List threads in a room
Apply JSON Patch operations to Storage
Resolve a thread
Update room properties
Send a binary Yjs update
Why LlamaIndex?
LlamaIndex agents combine Liveblocks tool responses with indexed documents for comprehensive, grounded answers. Connect 18 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
- —
Data-first architecture: LlamaIndex agents combine Liveblocks tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain Liveblocks tool calls with transformations, filters, and re-rankers in a typed pipeline
- —
Multi-source reasoning: agents can query Liveblocks, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Liveblocks tools were called, what data was returned, and how it influenced the final answer
Liveblocks in LlamaIndex
Liveblocks and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Liveblocks to LlamaIndex through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Liveblocks in LlamaIndex
The Liveblocks MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 18 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LlamaIndex only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Liveblocks for LlamaIndex
Every tool call from LlamaIndex to the Liveblocks MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I filter rooms by specific metadata using the AI?
You can ask the agent to use the list_rooms tool and provide a JSON string in the metadata parameter. For example, ask to 'List rooms where the project metadata is alpha'.
Can I generate a temporary access token for a user to join a room?
Yes. Use the authorize_user tool. Provide the Room ID and User ID, and the agent will return a token that grants access to that specific room.
Is it possible to permanently delete a room and its data?
Yes, the delete_room tool allows you to permanently remove a room and all associated storage, comments, and metadata. Use this with caution as it is irreversible.
How does LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query Liveblocks tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp
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