How to Use the Uniphore Conversation AI MCP in Cursor

Q: How do I search meetings using Uniphore Conversation AI in Cursor?

Just call searchmeetings and pass the keyword or topic. The agent returns meeting IDs, which you can then use as variables in your code block.

Q: Can I list all available meetings for Uniphore Conversation AI in Cursor?

You use listmeetings to get a comprehensive overview of every recorded meeting ID. This lets your agent build out dependency graphs or iterate over multiple data sources.

Q: Does Uniphore Conversation AI require project setup for Cursor?

Yes, you create a .cursor/mcp.json file in the project root to define the server connection. You must enable Agent mode in chat for it to work.

Q: How do I get analytics data using Uniphore Conversation AI in Cursor?

You call getmeetinganalytics, passing a valid meeting ID. The agent then takes the resulting metrics and lets you use them directly in your code's logic.

Inject live meeting data into your code using the Cursor AI editor.

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Connect Uniphore Conversation AI MCP to Cursor

Create your Vinkius account to connect Uniphore Conversation AI 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 Uniphore Conversation AI with Cursor

Ask AI about this MCP

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Claude

Perplexity

Write code based on action items

The `get_action_items` tool extracts tasks from a call, giving you clean input for coding. Instead of manually transcribing requirements, the agent hands you structured data directly into your project context. You can use this list alongside `search_meetings` to ensure your code solves the exact problem discussed in the meeting.

Reference call summaries while coding

Need quick background info on a feature? The `get_meeting_summary` tool retrieves an AI-generated summary. You can use this live text context to write accurate, requirement-aligned code. This means your agent generates working functions based on real API responses, not just placeholders.

Get full conversation transcripts

When you're debugging or building a feature related to a specific call, the `get_transcript` tool provides the whole text. You can feed this data into your code for parsing or validation. This direct access means your agent knows exactly what was said during development discussions.

Setup guide

Set up Uniphore Conversation AI 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 Uniphore Conversation AI 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 Uniphore Conversation AI transactions." If the MCP tools are loaded correctly, Cursor will call the Uniphore Conversation AI tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "uniphore-conversation-ai-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about Uniphore Conversation AI MCP in Cursor

Just call `search_meetings` and pass the keyword or topic. The agent returns meeting IDs, which you can then use as variables in your code block.

The server handles transcripts, summaries, action items, and analytics. Your agent treats these conversation elements like live API results, injecting them into the code you write.

You use `list_meetings` to get a comprehensive overview of every recorded meeting ID. This lets your agent build out dependency graphs or iterate over multiple data sources.

Yes, you create a `.cursor/mcp.json` file in the project root to define the server connection. You must enable Agent mode in chat for it to work.

You call `get_meeting_analytics`, passing a valid meeting ID. The agent then takes the resulting metrics and lets you use them directly in your code's logic.

Use it with your favorite AI tools

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