How to Use the Tolstoy MCP in LlamaIndex

Q: Can I track webhooks using Tolstoy and LlamaIndex?

Absolutely. By indexing the results of listwebhooks, you create a permanent, searchable record of every webhook endpoint used. This is crucial for auditing configurations without needing to call the tool again.

Q: Does Tolstoy support video uploads for LlamaIndex?

You can certainly upload content using uploadvideo. While the primary benefit isn't in the upload itself, indexing the resulting asset ID and metadata allows you to track that specific file’s history.

Index your video funnels: Query Tolstoy data using LlamaIndex and its MCP Server.

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Connect Tolstoy MCP to LlamaIndex

Create your Vinkius account to connect Tolstoy 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 Tolstoy with LlamaIndex

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Search Video Analytics Data

You can index performance metrics into a knowledge base for later recall. Running `get_video_analytics` captures the raw numbers, but by indexing that output, you create searchable insights. Later, your RAG application queries past trends and specific metric ranges rather than just viewing a dashboard.

Query Asset Metadata

Never forget where you stored something again. By running `list_videos` or `list_folders`, the output metadata gets indexed into your vector store. This means you can ask, 'What were the titles of videos in Folder X?' and get an answer grounded in that exact API data.

Track Project Configurations

LlamaIndex lets you save knowledge about complex setups. When you use `list_interactive_projects`, the resulting project structure is indexed. This allows your application to retrieve details of a specific funnel's setup from past sessions, which is much better than relying on memory.

Setup guide

Set up Tolstoy 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 Tolstoy 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 Tolstoy tools.",
)
response = await agent.run("List recent Tolstoy data")

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Common questions about Tolstoy MCP in LlamaIndex

LlamaIndex makes the data searchable. Instead of just seeing a list from `list_videos`, you can ask, 'What was the average view time on our videos last quarter?' and it grounds the answer in that API result.

The perfect fit is combining live API data with documents. For instance, you can combine a marketing PDF with the latest metrics from `get_video_analytics` to generate an executive summary.

Absolutely. By indexing the results of `list_webhooks`, you create a permanent, searchable record of every webhook endpoint used. This is crucial for auditing configurations without needing to call the tool again.

You can certainly upload content using `upload_video`. While the primary benefit isn't in the upload itself, indexing the resulting asset ID and metadata allows you to track that specific file’s history.

This server touches video performance analytics, folder structures, and webhook configuration. You are indexing structured data like metrics from `get_video_analytics` and lists from `list_webhooks`.

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