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Customers.ai MCP Server for LangChainGive LangChain instant access to 8 tools to Add Tag To Contact, Get Contact, List Xray Leads, and more

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Customers.ai 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 Customers.ai app connector for LangChain is a standout in the Productivity category — giving your AI agent 8 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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

asyncio.run(main())
Customers.ai
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 Customers.ai MCP Server

Connect your Customers.ai (formerly MobileMonkey) account to any AI agent and take full control of your automated messaging and B2B identity resolution workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Customers.ai 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

  • Contact Orchestration — List and search your contact database programmatically, retrieving detailed metadata from identity resolution pipelines like X-Ray Pixel
  • Multichannel Engagement — Programmatically dispatch plain text or high-fidelity JSON messages (including galleries and buttons) across SMS and chat channels
  • Identity Resolution Intelligence — Access leads identified through website visits to prioritize high-intent prospects and maintain a high-fidelity sales pipeline
  • Attribute Management — Programmatically update custom contact attributes and manage audience segments through dynamic tagging directly from your agent
  • Lead Discovery — Find contacts by email, phone, or external identifiers to perfectly coordinate your multichannel outreach and follow-ups

The Customers.ai 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.

All 8 Customers.ai tools available for LangChain

When LangChain connects to Customers.ai through Vinkius, your AI agent gets direct access to every tool listed below — spanning customersai, identity-resolution, messaging-automation, 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_tag_to_contact

Add a tag to a contact

get_contact

Get contact profile details

list_xray_leads

List identified website visitors

remove_tag_from_contact

Remove a tag from a contact

search_contacts

Search for contacts in Customers.ai

send_rich_message

Send a structured JSON message

send_text_message

Send a text message to a contact

update_contact_attributes

Update attributes for a contact

Connect Customers.ai to LangChain via MCP

Follow these steps to wire Customers.ai into LangChain. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save the code and run python agent.py
04

Explore tools

The agent discovers 8 tools from Customers.ai via MCP

Why Use LangChain with the Customers.ai MCP Server

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

01

The largest ecosystem of integrations, chains, and agents. combine Customers.ai MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across Customers.ai queries for multi-turn workflows

Customers.ai + LangChain Use Cases

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

01

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

02

Autonomous research agents: LangChain agents query Customers.ai, synthesize findings, and generate comprehensive research reports

03

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

04

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

Example Prompts for Customers.ai in LangChain

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

01

"List the last 5 leads identified via X-Ray Pixel."

02

"Find the contact with email 'jane.doe@example.com'."

03

"Add the 'Q2 Campaign' tag to contact ID '1024'."

Troubleshooting Customers.ai MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Customers.ai + LangChain FAQ

Common questions about integrating Customers.ai MCP Server with LangChain.

01

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.
02

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.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.