ChatFly MCP Server for LangChainGive LangChain instant access to 7 tools to Chat, Create Bot, Get Bot, and more
LangChain is the leading Python framework for composable LLM applications. Connect ChatFly 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 ChatFly app connector for LangChain is a standout in the Customer Support category — giving your AI agent 7 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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({
"chatfly-alternative": {
"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 ChatFly, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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 ChatFly MCP Server
Connect your ChatFly account to any AI agent and take full control of your custom chatbot orchestration and automated knowledge ingestion workflows through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with ChatFly through native MCP adapters. Connect 7 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 Orchestration — Create and manage multiple high-fidelity AI chatbot instances programmatically, including configuring welcome messages and internal metadata
- Knowledge Ingestion — Programmatically train your bots by uploading website URLs and documents to coordinate an accurate, data-driven knowledge base
- Real-Time Interaction — Send messages and retrieve AI responses from specific bots to test performance or integrate chat into custom business applications
- Source Management — Access and monitor your complete directory of data sources (URLs, docs) to oversee the information feeding your digital assistants
- Operational Monitoring — Track chatbot performance, session histories, and account-level status directly through your agent for instant reporting
The ChatFly MCP Server exposes 7 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 7 ChatFly tools available for LangChain
When LangChain connects to ChatFly through Vinkius, your AI agent gets direct access to every tool listed below — spanning chatbot-builder, conversational-ai, lead-qualification, 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.
Interact with a chatbot
Provide name and welcome message. Create a new chatbot
Get details of a specific bot
List all chatbots
List data sources for a bot
Update an existing bot
Add a knowledge source to a bot
Connect ChatFly to LangChain via MCP
Follow these steps to wire ChatFly into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install langchain langchain-mcp-adapters langgraph langchain-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
python agent.pyExplore tools
Why Use LangChain with the ChatFly MCP Server
LangChain provides unique advantages when paired with ChatFly through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine ChatFly 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 ChatFly queries for multi-turn workflows
ChatFly + LangChain Use Cases
Practical scenarios where LangChain combined with the ChatFly MCP Server delivers measurable value.
RAG with live data: combine ChatFly tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query ChatFly, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain ChatFly tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every ChatFly tool call, measure latency, and optimize your agent's performance
Example Prompts for ChatFly in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with ChatFly immediately.
"List all my available chatbots in ChatFly."
"Train 'bot_1' by ingesting 'https://vinkius.com/faq'."
"Ask 'bot_1': 'What are your support hours?'."
Troubleshooting ChatFly MCP Server with LangChain
Common issues when connecting ChatFly to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersChatFly + LangChain FAQ
Common questions about integrating ChatFly MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.