SleekFlow MCP Server for LangChain 7 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect SleekFlow 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({
"sleekflow": {
"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 SleekFlow, 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 SleekFlow MCP Server
Connect your SleekFlow platform to any AI agent to power up your conversational support, sales, and marketing. Read real-time chat threads spanning across multiple digital channels and dispatch replies without leaving your chat interface.
LangChain's ecosystem of 500+ components combines seamlessly with SleekFlow 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
- Unified Conversations — Track and retrieve ongoing chat histories across WhatsApp, Instagram, Telegram, and WeChat
- Direct Messaging — Compose and send outbound responses or proactive messages back to customers seamlessly
- Contact Management — List all synced contacts and get their deep profile metadata including CRM ties
- Chat Segmentation — View categorization labels to segment hot leads or identify VIP support customers
- Automation Overviews — Retrieve a list of your configured automation workflows and active chatbot trees
The SleekFlow 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.
How to Connect SleekFlow to LangChain via MCP
Follow these steps to integrate the SleekFlow 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 7 tools from SleekFlow via MCP
Why Use LangChain with the SleekFlow MCP Server
LangChain provides unique advantages when paired with SleekFlow through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine SleekFlow 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 SleekFlow queries for multi-turn workflows
SleekFlow + LangChain Use Cases
Practical scenarios where LangChain combined with the SleekFlow MCP Server delivers measurable value.
RAG with live data: combine SleekFlow tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query SleekFlow, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain SleekFlow tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every SleekFlow tool call, measure latency, and optimize your agent's performance
SleekFlow MCP Tools for LangChain (7)
These 7 tools become available when you connect SleekFlow to LangChain via MCP:
get_contact_details
Retrieves details for a specific contact
list_automation_flows
Lists available automation flows
list_channels
Lists all connected communication channels
list_contact_labels
Lists all labels used for contact categorization
list_contacts
Lists all contacts in SleekFlow
list_conversations
Lists all conversations across channels
send_message
Sends a message in a conversation
Example Prompts for SleekFlow in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with SleekFlow immediately.
"Show me all unread conversations from this weekend."
"Send a reply to conversation conv-xxxx saying 'Your refund has been processed. It will appear in 3-5 business days.'"
Troubleshooting SleekFlow MCP Server with LangChain
Common issues when connecting SleekFlow to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersSleekFlow + LangChain FAQ
Common questions about integrating SleekFlow 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 SleekFlow 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 SleekFlow to LangChain
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.