AeroLeads MCP Server for LangChainGive LangChain instant access to 12 tools to Add New Lead, Delete Lead, Find Email By Name, and more
LangChain is the leading Python framework for composable LLM applications. Connect AeroLeads 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 AeroLeads app connector for LangChain is a standout in the Sales Automation category — giving your AI agent 12 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({
"aeroleads": {
"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 AeroLeads, 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 AeroLeads MCP Server
Connect your AeroLeads account to any AI agent and take full control of your B2B lead generation and high-fidelity contact enrichment workflows through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with AeroLeads through native MCP adapters. Connect 12 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
- Verified Email Orchestration — Instantly find professional email addresses using prospect names and company domains with high-fidelity verification status
- LinkedIn Enrichment Intelligence — Programmatically retrieve over 60 data points from LinkedIn URLs, including verified phone numbers, job roles, and skills
- Prospect Lifecycle Management — List and manage your captured leads programmatically, or create new high-fidelity records directly through your agent
- Domain Discovery Architecture — Find all professional contacts associated with a specific company domain to identify key decision-makers programmatically
- Operational Monitoring — Track your remaining account credits and monitor team activity directly through your agent for instant performance reporting
The AeroLeads MCP Server exposes 12 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 12 AeroLeads tools available for LangChain
When LangChain connects to AeroLeads through Vinkius, your AI agent gets direct access to every tool listed below — spanning b2b-prospecting, email-verification, lead-enrichment, 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.
Manually add lead
Remove captured lead
Find email by name
Get profile info
Get credit status
Get full lead info
Enrich LinkedIn profile
List your leads
List lead lists
List account users
List active webhooks
Find leads in domain
Connect AeroLeads to LangChain via MCP
Follow these steps to wire AeroLeads 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 AeroLeads MCP Server
LangChain provides unique advantages when paired with AeroLeads through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine AeroLeads 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 AeroLeads queries for multi-turn workflows
AeroLeads + LangChain Use Cases
Practical scenarios where LangChain combined with the AeroLeads MCP Server delivers measurable value.
RAG with live data: combine AeroLeads tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query AeroLeads, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain AeroLeads tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every AeroLeads tool call, measure latency, and optimize your agent's performance
Example Prompts for AeroLeads in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with AeroLeads immediately.
"Find the email for 'Elon Musk' at 'tesla.com'."
"Enrich the profile for this LinkedIn URL: 'https://linkedin.com/in/example'."
"Search for all leads in the 'vinkius.com' domain."
Troubleshooting AeroLeads MCP Server with LangChain
Common issues when connecting AeroLeads to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersAeroLeads + LangChain FAQ
Common questions about integrating AeroLeads 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.