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ChartMogul MCP Server for CrewAIGive CrewAI instant access to 12 tools to Create Customer Record, Get Api Status, Get Arr History, and more

Built by Vinkius GDPR 12 Tools Framework

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

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The ChartMogul app connector for CrewAI is a standout in the Data Analytics category — giving your AI agent 12 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="ChartMogul Specialist",
    goal="Help users interact with ChartMogul effectively",
    backstory=(
        "You are an expert at leveraging ChartMogul 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 ChartMogul "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 12 available tools "
        "and what they can do."
    ),
)

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

Connect your ChartMogul account to any AI agent and take full control of your SaaS revenue intelligence and subscription monitoring workflows through natural conversation.

When paired with CrewAI, ChartMogul becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call ChartMogul 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

  • Revenue Orchestration — Retrieve real-time metrics for Monthly Recurring Revenue (MRR), Annual Run Rate (ARR), and Average Revenue Per Account (ARPA) programmatically
  • Churn & Retention Intelligence — Monitor customer churn rates and LTV (Lifetime Value) metrics across custom time intervals to understand your business health in real-time
  • Customer Lifecycle Management — List and manage your subscriber base programmatically, including retrieving detailed historical profiles and MRR contributions
  • Infrastructure Monitoring — Access information about your connected data sources (Stripe, Braintree, etc.) and subscription plans to ensure high-fidelity billing oversight
  • Trend Analysis — Query historical metrics over specific periods (day, week, month, quarter) to identify growth patterns and seasonal shifts directly through your agent

The ChartMogul MCP Server exposes 12 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 12 ChartMogul tools available for CrewAI

When CrewAI connects to ChartMogul through Vinkius, your AI agent gets direct access to every tool listed below — spanning mrr-tracking, saas-analytics, churn-analysis, 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.

create_customer_record

Add new customer

get_api_status

Check connection

get_arr_history

Analyze ARR

get_churn_rates

Analyze retention

get_customer_count_history

Monitor user growth

get_customer_details

Get customer profile

get_customer_ltv

Check Customer LTV

get_mrr_history

Analyze MRR

get_summary_metrics

Get key SaaS metrics

list_customers

List SaaS customers

list_data_sources

) connected to ChartMogul. List connected sources

list_subscription_plans

List billing plans

Connect ChartMogul to CrewAI via MCP

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

01

Install CrewAI

Run pip install crewai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
03

Customize the agent

Adjust the role, goal, and backstory to fit your use case
04

Run the crew

Run python crew.py. CrewAI auto-discovers 12 tools from ChartMogul

Why Use CrewAI with the ChartMogul MCP Server

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

01

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

02

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

03

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

04

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

ChartMogul + CrewAI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for ChartMogul in CrewAI

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

01

"Show our MRR and ARR summary for the last 3 months."

02

"What is our current churn rate compared to last month?"

03

"Get the MRR contribution for customer 'john.doe@example.com'."

Troubleshooting ChartMogul MCP Server with CrewAI

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

01

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.
02

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".
03

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.
04

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.

ChartMogul + CrewAI FAQ

Common questions about integrating ChartMogul MCP Server with CrewAI.

01

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.
02

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.
03

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.
04

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.
05

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.