Is this the same as VWO?

Howuku was acquired by VWO. This MCP uses the Howuku API which is now part of the VWO ecosystem.

How do I get my Howuku API Key?

You can find your API key in your Howuku/VWO dashboard under Account Settings > API Keys.

Can I see session recordings?

The list_recordings tool provides metadata and links to view session recordings for your projects.

Howuku MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Howuku
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Howuku through Vinkius, pass the Edge URL in the `mcps` parameter and every Howuku tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Howuku Specialist",
    goal="Help users interact with Howuku effectively",
    backstory=(
        "You are an expert at leveraging Howuku tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Howuku "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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About Howuku MCP Server

Empower your AI agents to analyze user behavior on your websites. This MCP server connects to Howuku (now part of VWO) to list projects, retrieve session recordings, view heatmaps, and monitor user feedback and surveys. Perfect for UX researchers and product managers.

When paired with CrewAI, Howuku becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Howuku tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

The Howuku MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI 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 Howuku to CrewAI via MCP

Follow these steps to integrate the Howuku MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Howuku

Why Use CrewAI with the Howuku MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Howuku through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Howuku + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Howuku MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Howuku for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Howuku, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Howuku tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Howuku against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Howuku MCP Tools for CrewAI (10)

These 10 tools become available when you connect Howuku to CrewAI via MCP:

get_me

Gets current authenticated user info

get_project

Retrieves details for a specific project

list_events

Lists custom tracking events for a project

list_feedback

Lists visual feedback items for a project

list_funnels

Lists conversion funnels for a project

list_heatmaps

Lists heatmaps for a project

list_organizations

Lists organizations associated with your account

list_projects

Lists Howuku projects (sites)

list_recordings

Lists session recordings for a project

list_surveys

Lists surveys for a project

Example Prompts for Howuku in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Howuku immediately.

"List all my Howuku projects."

"Show me recent session recordings for project ID 123."

"Check for any new user feedback on my site."

Troubleshooting Howuku MCP Server with CrewAI

Common issues when connecting Howuku to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Howuku + CrewAI FAQ

Common questions about integrating Howuku MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.