Hotjar (Behavior Analytics) MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Hotjar (Behavior Analytics) through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
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({
"hotjar-behavior-analytics": {
"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 Hotjar (Behavior Analytics), 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 Hotjar (Behavior Analytics) MCP Server
Connect your Hotjar account to any AI agent and take full control of your behavior analytics and user feedback through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Hotjar (Behavior Analytics) 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
- Site Management — List all registered sites and extract high-level details including tracking status and plan information directly from your agent
- Survey Analysis — Retrieve individual responses from active surveys, including detailed answers, timestamps, and device metadata to understand user sentiment
- Feedback Monitoring — Enumerate feedback widgets and pull discrete ratings, comments, and screenshots to identify friction points in your user journey
- GDPR Compliance — Look up specific user profiles and session counts, and execute right-to-erasure requests to delete user data securely
- Organization Audit — Navigate across different Hotjar organizations and retrieve site lists and member counts to manage multi-tenant environments efficiently
The Hotjar (Behavior Analytics) 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.
How to Connect Hotjar (Behavior Analytics) to LangChain via MCP
Follow these steps to integrate the Hotjar (Behavior Analytics) MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 10 tools from Hotjar (Behavior Analytics) via MCP
Why Use LangChain with the Hotjar (Behavior Analytics) MCP Server
LangChain provides unique advantages when paired with Hotjar (Behavior Analytics) through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Hotjar (Behavior Analytics) 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 Hotjar (Behavior Analytics) queries for multi-turn workflows
Hotjar (Behavior Analytics) + LangChain Use Cases
Practical scenarios where LangChain combined with the Hotjar (Behavior Analytics) MCP Server delivers measurable value.
RAG with live data: combine Hotjar (Behavior Analytics) tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Hotjar (Behavior Analytics), synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Hotjar (Behavior Analytics) tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Hotjar (Behavior Analytics) tool call, measure latency, and optimize your agent's performance
Hotjar (Behavior Analytics) MCP Tools for LangChain (10)
These 10 tools become available when you connect Hotjar (Behavior Analytics) to LangChain via MCP:
get_heatmap
Get heatmap details
get_site
Get current site details
get_survey
Get survey details
list_feedback
List incoming feedback
list_funnels
List conversion funnels
list_heatmaps
List all heatmaps
list_recordings
List session recordings
list_sites
List all tracked sites
list_survey_responses
List survey responses
list_surveys
List all surveys
Example Prompts for Hotjar (Behavior Analytics) in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Hotjar (Behavior Analytics) immediately.
"List all surveys for our main marketing site"
"Show me the last 5 responses for survey ID 123"
"How many responses has our 'NPS Widget' received so far?"
Troubleshooting Hotjar (Behavior Analytics) MCP Server with LangChain
Common issues when connecting Hotjar (Behavior Analytics) to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersHotjar (Behavior Analytics) + LangChain FAQ
Common questions about integrating Hotjar (Behavior Analytics) 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.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Hotjar (Behavior Analytics) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
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Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
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TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Hotjar (Behavior Analytics) to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.