Can I see my current MRR through the agent?

Yes! Use the `get_mrr_metrics` tool with a start and end date. The agent will return the MRR data for that period directly from ChartMogul.

How do I check the subscription status of a specific customer?

First, use `list_mogul_customers` to find the customer's UUID, then use the `get_mogul_customer_details` tool to see their active plans and history.

Where do I find my ChartMogul API Key?

Log in to your ChartMogul account and go to **Settings > API Keys**. You can create and copy your API key from there.

ChartMogul MCP Server for CrewAI 8 tools — connect in under 2 minutes

Name: ChartMogul
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 8 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.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

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 8 available tools "
        "and what they can do."
    ),
)

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

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* 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 subscription analytics through natural conversation. Access real-time SaaS metrics like MRR, ARR, and Churn Rate.

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

Metrics Oversight — Retrieve all high-level subscription metrics (MRR, ARR, ARPA, ASP) natively
Growth Intelligence — Access detailed customer count and churn rate data flawlessly
Customer Deep-Dives — List and retrieve complete profiles for any customer in your database securely
Data Logistics — List and audit all configured data sources providing information to your account flawlessly
Revenue Analysis — Track MRR and ARR trends over specific timeframes directly within your workspace
System Verification — Verify API connectivity and account status using the built-in ping and diagnostic tools

The ChartMogul MCP Server exposes 8 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 ChartMogul to CrewAI via MCP

Follow these steps to integrate the ChartMogul 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 8 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.

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

ChartMogul + CrewAI Use Cases

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

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

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

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

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

ChartMogul MCP Tools for CrewAI (8)

These 8 tools become available when you connect ChartMogul to CrewAI via MCP:

get_arr_metrics

Retrieve Annualized Run Rate metrics

get_customer_count_metrics

Retrieve total customer count metrics over time

get_mogul_customer_details

Get detailed information for a specific customer

get_mrr_metrics

Retrieve Monthly Recurring Revenue metrics

get_subscription_metrics

Retrieve all high-level subscription metrics (MRR, ARR, etc)

list_mogul_customers

List all customers in ChartMogul

list_mogul_data_sources

List all data sources configured in the account

ping_mogul_api

Verify connectivity and authentication with the ChartMogul API

Example Prompts for ChartMogul in CrewAI

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

"What is my total MRR for the last 3 months?"

"Show me details for customer UUID 'cust_123456'."

"Get my subscription metrics for 2024-01-01 to 2024-03-31."

Troubleshooting ChartMogul MCP Server with CrewAI

Common issues when connecting ChartMogul 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.

ChartMogul + CrewAI FAQ

Common questions about integrating ChartMogul 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.