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zipperHQ MCP Server for LangChainGive LangChain instant access to 10 tools to Check Zipper Status, Get Account, Get Contact Views, and more

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect zipperHQ 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 zipperHQ app connector for LangChain is a standout in the Communication Messaging category — giving your AI agent 10 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({
        "zipperhq": {
            "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 zipperHQ, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
zipperHQ
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 zipperHQ MCP Server

Connect your zipperHQ account to any AI agent and take full control of your video email orchestration and automated personalized messaging through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with zipperHQ through native MCP adapters. Connect 10 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

  • Video Portfolio Orchestration — List and manage your entire high-fidelity portfolio of video emails programmatically, retrieving detailed technical metadata and SKU IDs
  • Recording & Status Intelligence — Programmatically monitor real-time recording statuses (Pending, Uploaded, Ready) to maintain a perfectly coordinated content pipeline
  • Engagement Monitoring — Access real-time status updates for video views (e.g., 'Last Viewed') and track individual recipient interaction directly through your agent
  • Metadata Management — Programmatically retrieve high-fidelity video durations and session IDs to maintain a perfectly coordinated media record
  • Operational Monitoring — Verify account-level API connectivity and monitor video orchestration volume directly through your agent for perfectly coordinated service scaling

The zipperHQ MCP Server exposes 10 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 10 zipperHQ tools available for LangChain

When LangChain connects to zipperHQ through Vinkius, your AI agent gets direct access to every tool listed below — spanning video-email, personalized-messaging, engagement-tracking, 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.

check_zipper_status

Verify ZipperHQ API connectivity

get_account

Get your ZipperHQ account info

get_contact_views

Get video views for a specific contact

get_recent_videos

Get the 10 most recent videos

get_video

Get details of a specific video

get_video_analytics

Get analytics for a specific video

list_contacts

List all video recipients

list_recordings

List all screen recordings

list_videos

List all video emails

search_videos

Search videos by keyword

Connect zipperHQ to LangChain via MCP

Follow these steps to wire zipperHQ 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 10 tools from zipperHQ via MCP

Why Use LangChain with the zipperHQ MCP Server

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

01

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

zipperHQ + LangChain Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for zipperHQ in LangChain

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

01

"List all video emails sent today in my zipperHQ account."

02

"Show the view duration for the last video sent to 'Acme Corp'."

03

"Check for any video emails with 'Pending' recording status."

Troubleshooting zipperHQ MCP Server with LangChain

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

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

zipperHQ + LangChain FAQ

Common questions about integrating zipperHQ 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.