How to Use the Uniphore Conversation AI MCP in Cline

Q: Can Cline use Uniphore Conversation AI for large-scale topic analysis?

Yes. By calling listtopics, you can get an exhaustive list of all tracked keywords across your organization, which is perfect for building a centralized taxonomy service in your codebase.

Q: If I use Uniphore Conversation AI with Cline, what kind of data can I retrieve?

You get structured data: meeting IDs (listmeetings), full transcripts (gettranscript), and analytical insights. This is ideal for backend processing where you need predictable JSON output.

Build a dashboard from call data. Cline executes Uniphore Conversation AI tasks in the terminal for you.

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Connect Uniphore Conversation AI MCP to Cline

Create your Vinkius account to connect Uniphore Conversation AI to Cline 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 Cline

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Run Meeting Data Queries with MCP Server

Need to check meeting details? Start by running `list_meetings` to get all relevant IDs. Then, Cline can execute `get_meeting` or use `search_meetings` directly in your script to filter for specific discussions based on keywords. This lets you write a single command that pulls complex data structures without needing manual API calls.

Automate Action Item Extraction

Writing code around business logic is easy. Cline can take the output of `get_action_items` and use it as input for a new component, letting you build out records or reports based on who was assigned what task. It treats the extracted action items like any other data source in your terminal workflow.

Process Meeting Summaries via Cline

If you need to process a lot of meeting results, use `get_meeting_summary`. You can pipe this summary text directly into a script that validates the output or feeds it into another service for database ingestion. This makes the MCP Server data consumable by your backend code immediately.

Setup guide

Set up Uniphore Conversation AI MCP in Cline

Prerequisites

VS Code with Cline extension installed
Active Vinkius subscription with a valid endpoint token

1

Open Cline MCP settings

Click the Cline icon in the VS Code sidebar to open the Cline panel. Then click the MCP Servers icon (server stack) at the top-right corner of the panel.
2

Add a remote server

Click "Remote Servers" at the top, then click "Add Remote MCP". In the Name field, type uniphore-conversation-ai-mcp. In the URL field, paste your Vinkius endpoint: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp. Get your token from cloud.vinkius.com.
3

Enable the server

After saving, the server appears in the Cline MCP panel. Toggle the switch to enable it. The status indicator turns green when the connection is live.
4

Start using tools

Return to the Cline chat and ask: "Check my latest Uniphore Conversation AI refund status." Cline will discover the available tools and request your approval before invoking each one — giving you full control over every action.

Cline MCP Settings

{
  "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 Cline

You integrate it directly into your shell script. For example, you run `cline mcp get_action_items ` and pipe the JSON output straight into a file or another program to process the data.

Yes. By calling `list_topics`, you can get an exhaustive list of all tracked keywords across your organization, which is perfect for building a centralized taxonomy service in your codebase.

The MCP Server touches communication messaging data like transcripts and summaries. Since you're running this headless, all interaction is via the terminal, which gives maximum control over execution context.

You get structured data: meeting IDs (`list_meetings`), full transcripts (`get_transcript`), and analytical insights. This is ideal for backend processing where you need predictable JSON output.

This server provides access to communication messaging content, including meeting transcripts, analytics, and extracted action items. You use these types as input variables in your terminal scripts.

Use it with your favorite AI tools

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