Adversus MCP Server for LangChainGive LangChain instant access to 7 tools to Add Contact To Campaign, Get Campaign Details, List Account Users, and more
LangChain is the leading Python framework for composable LLM applications. Connect Adversus 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 Adversus app connector for LangChain is a standout in the Sales Automation category — giving your AI agent 7 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({
"adversus": {
"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 Adversus, 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 Adversus MCP Server
Connect your Adversus account to any AI agent and take full control of your outbound sales operations, telemarketing, and CRM orchestration through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Adversus 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
- Campaign Orchestration — List all telemarketing and outreach campaigns programmatically, retrieving detailed status, high-fidelity metadata, and performance metrics in real-time
- Lead Execution Intelligence — Programmatically add new contacts and leads to specific campaigns to coordinate your automated dialer and outreach strategy
- Contact Database Management — Access complete directories of leads and contacts assigned to campaigns, retrieving high-fidelity profile metadata and relationship history
- Project & Team Visibility — Access configured CRM projects and associated campaigns to maintain a perfectly coordinated sales pipeline
- Operational Monitoring — Access high-fidelity metadata for account agents and verify API connectivity directly through your agent for instant operational reporting
The Adversus 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.
All 7 Adversus tools available for LangChain
When LangChain connects to Adversus through Vinkius, your AI agent gets direct access to every tool listed below — spanning dialer, telemarketing, outbound-sales, 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.
Add a new contact to a campaign
Get details for a specific campaign
List team users
List global leads
List contacts in a campaign
List Adversus campaigns
List projects
Connect Adversus to LangChain via MCP
Follow these steps to wire Adversus 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 Adversus MCP Server
LangChain provides unique advantages when paired with Adversus through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Adversus 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 Adversus queries for multi-turn workflows
Adversus + LangChain Use Cases
Practical scenarios where LangChain combined with the Adversus MCP Server delivers measurable value.
RAG with live data: combine Adversus tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Adversus, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Adversus tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Adversus tool call, measure latency, and optimize your agent's performance
Example Prompts for Adversus in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Adversus immediately.
"List all active campaigns and their performance in Adversus."
"Add 'John Doe' (+15550123) to the 'New Business' campaign (ID: 'camp_456')."
"Show the last 5 leads captured across all my campaigns."
Troubleshooting Adversus MCP Server with LangChain
Common issues when connecting Adversus to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersAdversus + LangChain FAQ
Common questions about integrating Adversus 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.