Cliengo MCP Server for LangChain 8 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Cliengo 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 MCP SERVER
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({
"cliengo": {
"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 Cliengo, 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 Cliengo MCP Server
Connect your Cliengo account to any AI agent and take full control of your conversational marketing and lead management through natural conversation. Streamline how you capture and qualify leads via chatbot and WhatsApp natively.
LangChain's ecosystem of 500+ components combines seamlessly with Cliengo 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
- Lead Oversight — List and retrieve details for all leads and contacts captured via Cliengo natively
- Conversation Intelligence — Access all chatbot or WhatsApp conversations and retrieve full message histories flawlessly
- Website Tracking — List all websites and projects where your Cliengo chatbot is installed securely
- Message Auditing — Retrieve all specific messages exchanged with a contact to understand their needs flawlessly
- User Management — List internal users and agents who manage conversations within your account securely
- Webhook Visibility — Monitor all configured webhooks for real-time lead data integration directly within your workspace
The Cliengo 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 Cliengo to LangChain via MCP
Follow these steps to integrate the Cliengo 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 Cliengo via MCP
Why Use LangChain with the Cliengo MCP Server
LangChain provides unique advantages when paired with Cliengo through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Cliengo 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 Cliengo queries for multi-turn workflows
Cliengo + LangChain Use Cases
Practical scenarios where LangChain combined with the Cliengo MCP Server delivers measurable value.
RAG with live data: combine Cliengo tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Cliengo, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Cliengo tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Cliengo tool call, measure latency, and optimize your agent's performance
Cliengo MCP Tools for LangChain (8)
These 8 tools become available when you connect Cliengo to LangChain via MCP:
get_chat_history
Get the full message history for a specific conversation
get_contact_messages
Retrieve all messages exchanged with a specific contact
get_lead_details
Get detailed information for a specific contact
list_chat_conversations
List all chatbot or WhatsApp conversations
list_cliengo_leads
List all leads and contacts captured via Cliengo
list_cliengo_users
List all internal users and agents in the account
list_cliengo_webhooks
List all configured webhooks for real-time lead data
list_cliengo_websites
List all websites/projects where Cliengo is installed
Example Prompts for Cliengo in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Cliengo immediately.
"List all new leads from Cliengo today."
"Show me the chat history for Juan Perez."
"List all internal users who manage my Cliengo account."
Troubleshooting Cliengo MCP Server with LangChain
Common issues when connecting Cliengo to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersCliengo + LangChain FAQ
Common questions about integrating Cliengo 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 Cliengo 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 Cliengo to LangChain
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.