Can I train my bot with a new URL through the agent?

Yes! Use the `add_data_source` tool and provide the Bot ID and the target URL. The bot will automatically scrape and learn from that page.

How do I review the chat history of a specific user conversation?

First, use `list_conversations` to find the active sessions. Then, use `get_conversation_history` with the Conversation ID to retrieve the full log of messages.

Does the integration allow me to create a completely new bot?

Yes. Use the `create_bot` action and provide a name and a system prompt/instructions. The bot will be instantly created in your account.

Bot9 MCP Server for LangChain 8 tools — connect in under 2 minutes

Name: Bot9
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Bot9 through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "bot9": {
            "transport": "streamable_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,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Bot9, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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High SecurityEnterprise-grade

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DLPData protection

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Ed25519Audit chain

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Bot9 MCP Server

Connect your Bot9 account to any AI agent and orchestrate your customer support and conversational automation workflows through natural language.

LangChain's ecosystem of 500+ components combines seamlessly with Bot9 through native MCP adapters. Connect 8 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Bot Management — List all configured AI bots, retrieve specific configurations, and create new bots on the fly.
Training & Data Sources — List existing knowledge base sources and dynamically add new URLs for your bots to learn from.
Conversation Oversight — Retrieve active conversation lists and export historical chat logs for analysis.
Message Automation — Send messages to your bots programmatically to test responses or simulate user interactions.

The Bot9 MCP Server exposes 8 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Bot9 to LangChain via MCP

Follow these steps to integrate the Bot9 MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 8 tools from Bot9 via MCP

Why Use LangChain with the Bot9 MCP Server

LangChain provides unique advantages when paired with Bot9 through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Bot9 MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Bot9 queries for multi-turn workflows

Bot9 + LangChain Use Cases

Practical scenarios where LangChain combined with the Bot9 MCP Server delivers measurable value.

RAG with live data: combine Bot9 tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Bot9, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Bot9 tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Bot9 tool call, measure latency, and optimize your agent's performance

Bot9 MCP Tools for LangChain (8)

These 8 tools become available when you connect Bot9 to LangChain via MCP:

add_data_source

Add a URL to train the bot

create_bot

Create a new AI chatbot

get_bot

Get details of a specific bot

get_conversation_history

Retrieve message history of a conversation

list_bots

List all AI bots

list_conversations

List active conversations for a bot

list_data_sources

List knowledge base sources for a bot

send_message

Send a message to a bot and get a response

Example Prompts for Bot9 in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Bot9 immediately.

"List all bots in my Bot9 account."

"Add the URL https://example.com/pricing to bot_123's knowledge base."

"Get the chat history for conversation conv_789 on bot_123."

Troubleshooting Bot9 MCP Server with LangChain

Common issues when connecting Bot9 to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Bot9 + LangChain FAQ

Common questions about integrating Bot9 MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.