How to Use the Volcengine RTC MCP in Cursor

Q: How do I get room user lists using Volcengine RTC and Cursor?

The agent calls getroomusers and injects the resulting JSON array directly into your coding context. You can then iterate over that list to write logic for every participant.

Q: What is the mechanism for controlling streams with Volcengine RTC and Cursor?

You use explicit function calls: mutestream or unmutestream. You must pass 'audio' or 'video' as a parameter, which determines what stream your code is manipulating.

Q: Can I automate recording setups with Volcengine RTC and Cursor?

Yes. Your agent can sequence the calls: startcloudrecord, run the logic, then finish by calling stopcloudrecord. This creates a complete, automated data capture workflow.

Q: What does the MCP Server provide for stream transcoding?

It provides methods like starttranscode and stoptranscode. You wrap these calls in your code to manage when an MCU stream needs format conversion or termination.

Inject live RTC call data into your code using Cursor's Agent mode.

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Connect Volcengine RTC MCP to Cursor

Create your Vinkius account to connect Volcengine RTC to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Volcengine RTC with Cursor

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List users and manage attendance via the MCP Server

Need to validate who is in a meeting before writing a script? `get_room_users` pulls that list directly into your code context. You can also check overall room activity using `get_active_rooms`. This lets you write logic around user presence. When running Agent mode in Cursor, the AI uses this data—not mock values—to build functional, accurate calling code.

Transcode and record live streams for context

If your application needs specific stream formats or permanent records, you start by calling `start_transcode`. Later, you use `stop_transcode` when the process is complete. You can also initiate a backup recording with `start_cloud_record`. These tools allow you to write scripts that manage media pipelines and ensure data capture from any real-time session.

Control call flow using stream mute/unmute

The MCP Server gives your code control over the audio and video feeds. Use `mute_stream` to silence a track, specifying 'audio' or 'video'. To bring it back online, you run `unmute_stream`. This capability lets developers build complex communication logic into their projects within Cursor.

Setup guide

Set up Volcengine RTC MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the Volcengine RTC MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent Volcengine RTC transactions." If the MCP tools are loaded correctly, Cursor will call the Volcengine RTC tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "volcengine-rtc-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Volcengine RTC. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Volcengine RTC MCP in Cursor

The agent calls `get_room_users` and injects the resulting JSON array directly into your coding context. You can then iterate over that list to write logic for every participant.

You use explicit function calls: `mute_stream` or `unmute_stream`. You must pass 'audio' or 'video' as a parameter, which determines what stream your code is manipulating.

Yes. Your agent can sequence the calls: `start_cloud_record`, run the logic, then finish by calling `stop_cloud_record`. This creates a complete, automated data capture workflow.

It provides methods like `start_transcode` and `stop_transcode`. You wrap these calls in your code to manage when an MCU stream needs format conversion or termination.

It handles ephemeral real-time metadata, including user presence lists and the status of media streams (audio/video). This is critical for live context injection into your code.

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