How do I get an Auth Token for Fomo?

You can find your API token in your Fomo dashboard under Settings > Site > API Access.

Can I use the agent to create new notification designs?

Yes, you can use the 'create_template' tool to programmatically add new notification shells using the {{ variable }} syntax.

How do I push a purchase event to my feed via the agent?

Use the 'create_event' tool and provide the event_type_id along with metadata like first_name, city, and title.

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

Name: Fomo
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 11 Tools Framework

Connect your CrewAI agents to Fomo through Vinkius, pass the Edge URL in the `mcps` parameter and every Fomo 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="Fomo Specialist",
    goal="Help users interact with Fomo effectively",
    backstory=(
        "You are an expert at leveraging Fomo 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 Fomo "
        "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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High SecurityEnterprise-grade

IAMAccess control

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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 Fomo MCP Server

Connect your Fomo account to any AI agent to automate your social proof marketing and notification feeds through the Model Context Protocol (MCP). Fomo allows you to programmatically push real-time customer interactions, such as purchases or sign-ups, directly to your website's live feed. This MCP server enables you to manage your notification events, design new templates, and monitor integrations directly through natural conversation.

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

Key Features

Real-time Events — Push new customer interactions to your live feed and manage existing events instantly.
Template Design — Programmatically create and list notification templates to define how your social proof looks.
Event Monitoring — Retrieve paginated lists of recent events and fetch detailed metadata for specific notifications.
Integration Oversight — Monitor all active third-party integrations connected to your Fomo account.
Application Insights — Access metadata for your Fomo application to maintain full context of your marketing setup.
Clean Feed Management — Update or delete events from your feed directly through the agent.

The Fomo 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 Fomo to CrewAI via MCP

Follow these steps to integrate the Fomo 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 Fomo

Why Use CrewAI with the Fomo MCP Server

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

Fomo + CrewAI Use Cases

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

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

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

Fomo MCP Tools for CrewAI (11)

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

create_event

Push a new event to feed

create_template

Create a new template

delete_event

Remove event from feed

get_application_info

Get account attributes

get_event

Get event details

get_template

Get template details

list_events

List recent social proof events

list_integrations

List active integrations

list_push_messages

List sent messages

list_templates

List notification templates

update_event

Modify an existing event

Example Prompts for Fomo in CrewAI

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

"List the last 5 social proof events in my Fomo application."

"Push a new sign-up event for 'Alex' from 'San Francisco' using template ID '123'."

"List all active notification templates in my account."

Troubleshooting Fomo MCP Server with CrewAI

Common issues when connecting Fomo 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.

Fomo + CrewAI FAQ

Common questions about integrating Fomo 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.