How do I find my Mav API Key?

Log in to your Mav dashboard and navigate to Settings to find your API Key.

Can I trigger a playbook for a specific phone number?

Yes! Use the `trigger_playbook` tool and provide the playbook ID and the lead's phone number.

Absolutely. Your token is encrypted at rest and injected securely at runtime.

Mav MCP Server for LangChain 0 tools — connect in under 2 minutes

Name: Mav
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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

asyncio.run(main())

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 Mav MCP Server

Connect your Mav account to any AI agent and take full control of your conversational SMS automation through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Mav through native MCP adapters. Connect 0 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

Playbook Management — List and inspect AI-driven conversational playbooks
Lead Qualification — Trigger automated SMS conversations to qualify new leads instantly
Activity Monitoring — Track real-time events and outcomes from ongoing conversations
Lead Management — Retrieve detailed metadata and status for leads in your pipeline

The Mav MCP Server exposes 0 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 Mav to LangChain via MCP

Follow these steps to integrate the Mav 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 0 tools from Mav via MCP

Why Use LangChain with the Mav MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine Mav 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 Mav queries for multi-turn workflows

Mav + LangChain Use Cases

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

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

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

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

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

Example Prompts for Mav in LangChain

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

"List all my Mav playbooks."

"Trigger the 'Lead Qual' playbook for +1234567890."

"Show recent outcomes for lead ID 9876."

Troubleshooting Mav MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Mav + LangChain FAQ

Common questions about integrating Mav MCP Server with LangChain.

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.

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.