CHATFLY MCP Server for LangChain 8 tools — connect in under 2 minutes
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.
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Vinkius supports streamable HTTP and SSE.
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": {
"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 workflows through natural conversation. Train and monitor your own AI agents using your business data.
LangChain's ecosystem of 500+ components combines seamlessly with CHATFLY 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
- Chatbot Oversight — List and retrieve details for all custom AI chatbots in your account natively
- Knowledge Logistics — List all uploaded documents and data sources used for bot training flawlessly
- Training Automation — Trigger the training process for your chatbots to ingest new data securely
- Conversation Intelligence — Access recent chat conversations and full message history flawlessly
- Live Messaging — Send messages to your chatbots and receive AI-generated responses in real-time
- System Monitoring — Retrieve core account information and monitor your AI usage quotas directly within your workspace
The CHATFLY 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 CHATFLY to LangChain via MCP
Follow these steps to integrate the CHATFLY 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 CHATFLY via MCP
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
CHATFLY MCP Tools for LangChain (8)
These 8 tools become available when you connect CHATFLY to LangChain via MCP:
get_chatbot_details
Get detailed information for a specific chatbot
get_chatfly_account_info
Retrieve core account and quota information
get_conversation_history
Retrieve the message history for a specific conversation
list_chatfly_bots
List all AI chatbots in your account
list_fly_conversations
List recent chat conversations
list_uploaded_documents
List all files uploaded to the knowledge base
send_bot_message
Send a message to a chatbot and receive a response
trigger_bot_training
Trigger the training process for a chatbot
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 active chatbots in CHATFLY."
"Show me the last 5 conversations for bot 'Support Assistant'."
"Send a test message to bot ID 123: 'How do I reset my password?'"
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.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect CHATFLY with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect CHATFLY to LangChain
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.