How do I find my Maropost Account ID?

Your Account ID is the numeric ID found in your Maropost login URL or in your account settings.

Where do I find my Auth Token?

Go to Maropost Settings > API to generate and copy your Auth Token.

Is my data secure with this integration?

Yes. Your credentials are encrypted at rest and injected securely at runtime.

Maropost MCP Server for CrewAI 11 tools — connect in under 2 minutes

Name: Maropost
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 11 Tools Framework

Connect your CrewAI agents to Maropost through Vinkius, pass the Edge URL in the `mcps` parameter and every Maropost 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

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Maropost Specialist",
    goal="Help users interact with Maropost effectively",
    backstory=(
        "You are an expert at leveraging Maropost 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 Maropost "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 11 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 Maropost MCP Server

Connect your Maropost account to any AI agent and take full control of your marketing automation through natural conversation.

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

Contact Management — Get contact details, list contacts in specific lists, and create/update records
Campaign Management — List all campaigns and fetch detailed configuration and status
List Management — Query contact lists and their specific details
Automation & Reports — Access workflows and retrieve detailed performance reports

The Maropost MCP Server exposes 11 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 Maropost to CrewAI via MCP

Follow these steps to integrate the Maropost 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 11 tools from Maropost

Why Use CrewAI with the Maropost MCP Server

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

Maropost + CrewAI Use Cases

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

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

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

Maropost MCP Tools for CrewAI (11)

These 11 tools become available when you connect Maropost to CrewAI via MCP:

create_contact

Create or update a contact

get_campaign_details

Get campaign details by ID

get_contact

Get contact details by email

get_list_details

Get list details by ID

get_report_details

Get report details by ID

get_workflow_details

Get workflow details by ID

list_campaigns

List all campaigns

list_contacts_in_list

List contacts in a specific list

list_lists

List all contact lists

list_reports

List all reports

list_workflows

List all workflows

Example Prompts for Maropost in CrewAI

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

"Find contact details for john.doe@example.com."

"List all active campaigns in Maropost."

"Show performance report for campaign ID 987."

Troubleshooting Maropost MCP Server with CrewAI

Common issues when connecting Maropost 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.

Maropost + CrewAI FAQ

Common questions about integrating Maropost 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.