Can I calculate a customer's health score using my AI agent?

Yes! Use the `get_health_score` tool by providing the User ID. The agent will retrieve the real-time engagement score from Zengain.

How do I see high-level usage summary for a specific product?

Use the `get_analytics_summary` tool. You can optionally provide a Product ID to filter the metrics for that specific offering.

Is it possible to track a new custom event through this integration?

Yes, use the `track_event` action. Provide the User ID and the Event Name to record engagement data programmatically.

INSTANT PLUG AND PLAY

Zengain MCP Server for CrewAIGive CrewAI instant access to 10 tools to Get Analytics Summary, Get Health Score, Get Product, and more

Name: Zengain
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 10 Tools Framework

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

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

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The Zengain app connector for CrewAI is a standout in the Data Analytics 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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Zengain Specialist",
    goal="Help users interact with Zengain effectively",
    backstory=(
        "You are an expert at leveraging Zengain 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 Zengain "
        "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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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 Zengain MCP Server

Connect your Zengain (Nalpeiron Growth Platform) account to any AI agent and simplify your customer success and usage analytics workflows through natural conversation.

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

What you can do

Product Lifecycle — List all registered products and retrieve detailed configuration metadata
User Engagement — Query product users, inspect their profiles, and calculate real-time health scores
Usage Analytics — Get high-level analytics summaries and track custom events to monitor feature adoption
KPM Tracking — Monitor Key Product Milestones to identify successful onboarding and churn risks
System Monitoring — List configured webhooks to understand your integration data flow

The Zengain 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.

All 10 Zengain tools available for CrewAI

When CrewAI connects to Zengain through Vinkius, your AI agent gets direct access to every tool listed below — spanning customer-success, product-analytics, lead-scoring, 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.

get_analytics_summary

Get analytics summary

get_health_score

Get customer health score

get_product

Get details for a specific product

get_user_details

Get details for a specific user

list_events

List tracking events

list_kpms

List Key Product Milestones

list_products

List Zengain products

list_users

List product users

list_webhooks

List configured webhooks

track_event

Track a custom event

Connect Zengain to CrewAI via MCP

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

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 Zengain

Why Use CrewAI with the Zengain MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Zengain 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

Zengain + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Zengain 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 Zengain, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Zengain 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 Zengain against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Zengain in CrewAI

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

"List all products in my Zengain account."

"What is the health score for user 'customer_456'?"

"Show me a summary of usage analytics for this month."

Troubleshooting Zengain MCP Server with CrewAI

Common issues when connecting Zengain 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.

Zengain + CrewAI FAQ

Common questions about integrating Zengain 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.