How to Use the Whereby MCP in LlamaIndex

Q: How does Whereby help me track past meetings using LlamaIndex?

You use listactivemeetings to pull the list. This output gets indexed into your vector store, allowing you to query historical meeting records and configurations later on.

Q: What's the process for updating room themes with Whereby and LlamaIndex?

The developer calls getroomtheme first to retrieve the existing settings. Then, they execute updateroomtheme, making both the old theme details and the new hex code searchable parts of your knowledge base.

Q: Whereby/LlamaIndex: If I want to know about deleted recordings, how do I query that with LlamaIndex?

While deletecloudrecording is irreversible, the metadata surrounding the action (e.g., 'Recording X was slated for deletion') can be indexed if you pass that context into your RAG pipeline.

Turn Whereby call logs into searchable knowledge bases with LlamaIndex.

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Connect Whereby MCP to LlamaIndex

Create your Vinkius account to connect Whereby to LlamaIndex 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 Whereby with LlamaIndex

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Indexing Meeting Configurations

LlamaIndex doesn't just get data; it indexes it. When you use `get_room_theme`, the resulting visual theme settings (like color codes and logo details) become searchable knowledge chunks. Your RAG application can then answer questions like, 'What was the primary brand color used for Q3 training sessions?' The tool output is ingested into your index, meaning past API data—not just documents—powers your semantic search.

Tracking Meeting Lifecycles

Need to know what meetings were active yesterday? You use `list_active_meetings`, and that list is added to your knowledge base. This lets you query past sessions, even if they are no longer running. Similarly, calling `get_meeting_details` makes the join URL and expiration date part of a searchable record, allowing for historical context in your queries.

Managing Recordings as Searchable Assets

When you list recordings using `list_cloud_recordings`, those titles and metadata are indexed. This means you can ask the system to find 'all recordings related to Project X' without having to know the exact file name. Even when you use `get_recording_details` to pull download links, the context of that link remains searchable within your LlamaIndex application.

Setup guide

Set up Whereby MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Whereby MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Whereby tools.",
)
response = await agent.run("List recent Whereby data")

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Common questions about Whereby MCP in LlamaIndex

You use `list_active_meetings` to pull the list. This output gets indexed into your vector store, allowing you to query historical meeting records and configurations later on.

The developer calls `get_room_theme` first to retrieve the existing settings. Then, they execute `update_room_theme`, making both the old theme details and the new hex code searchable parts of your knowledge base.

While `delete_cloud_recording` is irreversible, the metadata surrounding the action (e.g., 'Recording X was slated for deletion') can be indexed if you pass that context into your RAG pipeline.

The primary data types handled are room names, ISO 8601 dates (for expiration), and visual theme configurations, which are all indexed by the MCP Server.

You pass past session metadata into your index. The agent can then search this knowledge base using the `get_meeting_details` structure to retrieve historical join URLs and expiration dates.

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