Mav MCP Server for LangChainGive LangChain instant access to 9 tools to Create Lead, Get Lead, Get Playbook, and more
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.
Ask AI about this App Connector for LangChain
The Mav app connector for LangChain is a standout in the Human Resources category — giving your AI agent 9 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({
"mav-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 Mav, 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 Mav MCP Server
Connect your Mav AI recruiting account to any AI agent and manage candidate screening through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Mav through native MCP adapters. Connect 9 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
- Candidate Screening — Trigger automated AI screening conversations
- SMS Campaigns — Launch and manage outbound SMS recruiting campaigns
- Lead Management — Browse candidates and their qualification status
- Engagement Tracking — Monitor open rates, reply rates, and drop-offs
- Interview Data — Access responses and screening transcripts
The Mav MCP Server exposes 9 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 9 Mav tools available for LangChain
When LangChain connects to Mav through Vinkius, your AI agent gets direct access to every tool listed below — spanning ai-recruiting, candidate-screening, sms-engagement, 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.
Create a lead and trigger a playbook
Get details for a specific lead
Get details for a specific playbook
List recent activities/events
List all leads
List all available Mav playbooks
Manually opt-out a lead
Stop a running playbook for a lead
Update an existing lead
Connect Mav to LangChain via MCP
Follow these steps to wire Mav 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 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.
"Show active SMS campaigns and completion rates."
"Launch a screening campaign for the new Warehouse Staff list."
"Show screening results and transcripts for qualified candidates."
Troubleshooting Mav MCP Server with LangChain
Common issues when connecting Mav to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersMav + LangChain FAQ
Common questions about integrating Mav 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.