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SmartChatAI MCP Server for LangChainGive LangChain instant access to 12 tools to Add Pdf To Knowledge Base, Add Text To Knowledge Base, Add Website To Knowledge Base, and more

Built by Vinkius GDPR 12 Tools Framework

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

Ask AI about this App Connector for LangChain

The SmartChatAI app connector for LangChain is a standout in the Industry Titans category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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({
        "smartchatai": {
            "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 SmartChatAI, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
SmartChatAI
Fully ManagedVinkius Servers
60%Token savings
High SecurityEnterprise-grade
IAMAccess control
EU AI ActCompliant
DLPData protection
V8 IsolateSandboxed
Ed25519Audit chain
<40msKill switch
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 SmartChatAI MCP Server

Connect your SmartChatAI account to any AI agent to automate your intelligent chatbot orchestration and lead collection. SmartChatAI provides a premier platform for building custom AI bots, and this integration allows you to retrieve chatbot metadata, manage knowledge bases via URL or PDF, and track conversational history through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with SmartChatAI through native MCP adapters. Connect 12 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

  • Chatbot Orchestration — List all managed AI bots and retrieve detailed profile metadata, including status and configuration programmatically.
  • Knowledge Base Lifecycle Management — Add new data sources (URL, PDF, Text) to your bots' knowledge base directly from the AI interface to ensure they are always informed.
  • Message & Reply Control — Send automated replies and retrieve detailed chat history to maintain high-quality customer interactions via natural language.
  • Web Scraper Automation — Trigger website scraping to ingest content into your AI models and ensure your bots have the latest information.
  • Operational Monitoring — Track system health, manage webhooks, and monitor bot activity to ensure your conversational platform is always optimized.

The SmartChatAI MCP Server exposes 12 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.

All 12 SmartChatAI tools available for LangChain

When LangChain connects to SmartChatAI through Vinkius, your AI agent gets direct access to every tool listed below — spanning chatbot-orchestration, knowledge-base, lead-collection, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

add_pdf_to_knowledge_base

Train bot using a PDF

add_text_to_knowledge_base

Train bot using raw text

add_website_to_knowledge_base

Train bot using a URL

check_api_health

Verify SmartChatAI API status

create_new_ai_bot

Requires a name and optional initial prompt. Provision a new AI agent

get_authenticated_user_profile

Get account profile

get_bot_chat_history

Retrieve conversation transcripts

get_chatbot_details

Get configuration for a specific bot

list_ai_chatbots

List all AI chatbots

list_configured_webhooks

List active webhooks

message_ai_chatbot

Send a message and get AI reply

scrape_domain_links

Discover and index domain links

Connect SmartChatAI to LangChain via MCP

Follow these steps to wire SmartChatAI into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 12 tools from SmartChatAI via MCP

Why Use LangChain with the SmartChatAI MCP Server

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

01

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

02

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

03

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

04

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

SmartChatAI + LangChain Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for SmartChatAI in LangChain

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

01

"List all active AI bots in my SmartChatAI account."

02

"Show me all active chatbot conversations with their resolution rates and average response times."

03

"Train the chatbot with 10 new FAQ entries about our refund and return policies."

Troubleshooting SmartChatAI MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

SmartChatAI + LangChain FAQ

Common questions about integrating SmartChatAI MCP Server with LangChain.

01

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.
02

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.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.