How to Use the Tolstoy MCP in LangChain

Q: Can I list webhooks using Tolstoy and LangChain?

Yes. You can execute the listwebhooks tool call within your LangChain agent's workflow. This lets the agent read all configured webhook endpoints before deciding which one to activate or check.

Q: Does Tolstoy support data uploads for LangChain?

Yes, you can upload a video using uploadvideo and then have that action become part of your chain's history. The agent treats the successful upload as an intermediate result it can act upon next.

Build multi-step video funnels with LangChain and your MCP Server.

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Connect Tolstoy MCP to LangChain

Create your Vinkius account to connect Tolstoy to LangChain 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 LangChain

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Orchestrate Video Uploading

When you need to deploy a new interactive experience, the chain handles the whole sequence. First, it checks existing assets using `list_videos` or finds the right directory with `list_folders`. Then, it uses `upload_video` and immediately follows up by pulling performance metrics via `get_video_analytics`, ensuring your agent knows if the content is ready for launch.

Manage Complex Video Assets

You can build a chain that first lists all possible project blueprints using `list_interactive_projects`. After reviewing these, you might use `list_webhooks` to check what external systems are already connected. This sequence lets your agent determine the optimal structure for deployment before making any changes.

Automate Funnel Connection

To connect Tolstoy to other services, you can run a multi-step process. The chain first verifies existing connections with `list_webhooks`. Next, it sends the required data payload by using one of those webhooks. Finally, your agent confirms success or failure by attempting to list current video assets again using `list_videos`.

Setup guide

Set up Tolstoy MCP in LangChain

Prerequisites

Python 3.10+ installed
langchain-mcp-adapters + langgraph packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install langchain-mcp-adapters langgraph langchain-openai. The MCP adapters package converts MCP tools into native LangChain BaseTool objects.
2

Connect via HTTP transport
Use MultiServerMCPClient with "transport": "http" pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create a ReAct agent
Pass the discovered tools to create_react_agent() from LangGraph. The agent automatically routes Tolstoy tool calls through the MCP protocol.
4

Run with any LLM
Swap ChatOpenAI for ChatAnthropic, ChatGoogleGenerativeAI, or any LangChain-compatible model. The MCP tools work identically across all providers.

agent.py

from langchain_mcp_adapters.client import MultiServerMCPClient
from langgraph.prebuilt import create_react_agent
from langchain_openai import ChatOpenAI

async with MultiServerMCPClient({
    "tolstoy-mcp": {
        "transport": "http",
        "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    }
}) as client:
    tools = client.get_tools()

    agent = create_react_agent(
        ChatOpenAI(model="gpt-4o"),
        tools,
    )
    result = await agent.ainvoke({
        "messages": "List recent Tolstoy transactions"
    })
    print(result["messages"][-1].content)

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Common questions about Tolstoy MCP in LangChain

The LangChain framework lets you build a process where the agent decides when and how to call `get_video_analytics`. It doesn't just pull the data; it feeds that performance metric directly into the next step of your reasoning chain.

Use LangChain when you need a multi-step decision. For example, if your agent needs to check if an asset exists (`list_videos`), and only *then* upload it (`upload_video`), that sequential logic belongs in a chain.

Yes. You can execute the `list_webhooks` tool call within your LangChain agent's workflow. This lets the agent read all configured webhook endpoints before deciding which one to activate or check.

Yes, you can upload a video using `upload_video` and then have that action become part of your chain's history. The agent treats the successful upload as an intermediate result it can act upon next.

This server primarily touches video performance analytics and webhook configuration data. Specifically, you're working with metrics from `get_video_analytics` and the list of endpoints retrieved via `list_webhooks`.

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