How to Use the BotGenuity MCP in LangChain

Q: Can a LangChain agent manage multiple BotGenuity bots at once?

Yes. The agent uses listchatbots to see all available bots and can switch between them dynamically based on the user's request.

Q: How does LangChain handle BotGenuity conversation histories?

The agent calls getconversationhistory to pull past messages into its prompt memory. This gives your agent the context of previous support sessions before generating a response.

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Connect BotGenuity MCP to LangChain

Create your Vinkius account to connect BotGenuity 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 BotGenuity with LangChain

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Build multi-step LangChain support chains

The `list_chatbots` tool pulls your active BotGenuity bots directly into your LangChain agent's execution path. This lets your agent inspect active deployments before deciding how to route a user's query. Once the agent selects a bot, it uses `get_chatbot_details` to read the specific configuration. Your chain now knows exactly what knowledge base the bot uses, preventing mismatched context during complex support routing.

Audit chat histories inside LangChain pipelines

The `get_conversation_history` tool pulls raw chat transcripts straight into your LangChain tracing runs. This MCP integration lets your agent read past interactions to understand what a customer asked before the current session started. By combining this with `list_chatbot_conversations`, your LangChain agents can map out customer journeys. You get a clear view of where automated bots succeeded and where they stalled, all monitored via LangSmith.

Route captured leads to external databases

The `list_captured_leads` tool extracts contact details gathered by your bots during live chats. Your LangChain agent can grab these leads and instantly format them for your CRM. If a lead needs immediate follow-up, the agent triggers `chat_with_bot` to send a targeted message. This keeps your sales pipeline moving without manual data entry.

Setup guide

Set up BotGenuity 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 BotGenuity 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({
    "botgenuity-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 BotGenuity transactions"
    })
    print(result["messages"][-1].content)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by BotGenuity. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about BotGenuity MCP in LangChain

Install the langchain-mcp-adapters package and initialize the MultiServerMCPClient with the Vinkius endpoint. You then call get_tools to pass the BotGenuity tools directly to your agent.

Yes. The agent uses `list_chatbots` to see all available bots and can switch between them dynamically based on the user's request.

The agent calls `get_conversation_history` to pull past messages into its prompt memory. This gives your agent the context of previous support sessions before generating a response.

Each tool call adds a brief network hop, but you can track the exact latency of `chat_with_bot` and other MCP tools using LangSmith tracing.

Your captured lead details and customer names never touch third-party servers. Vinkius runs the server in an isolated sandbox, meaning lead data goes straight to your LangChain environment over encrypted connections.

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