How to Use the Fomo MCP in CrewAI

Q: How do I connect Fomo to my CrewAI setup?

Pass the server URL directly into your agent's mcps array. For granular control, use MCPServerHTTP from crewai.mcp and apply a tool filter.

Q: Can I restrict which Fomo tools a CrewAI agent can use?

Yes. You can use toolfilter to give your research agent access to listevents while only allowing the execution agent to run createevent.

Command multi-agent e-commerce teams with the Fomo CrewAI integration.

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Connect Fomo MCP to CrewAI

Create your Vinkius account to connect Fomo to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Fomo with CrewAI

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Perplexity

Autonomous Social Proof Teams

`list_events` and `create_event` enable your CrewAI agents to manage your notification feed entirely on their own through this MCP setup. You assign one agent to monitor your store's checkout database and another to format and push the data. They pass context through shared memory, ensuring no duplicate events get created. This hierarchical setup keeps your e-commerce operations running without manual input. A manager agent reviews the proposed notifications, verifies them against active rules, and greenlights the final push to your live feed.

Template Analysis and Auditing via MCP Server

`list_templates` and `get_template` let your research agents audit your current notification designs. An agent can pull every active template, analyze the variable structure, and suggest copy improvements based on conversion metrics. When a new layout gets approved, a separate execution agent uses `create_template` to push it live. The AI client handles the entire lifecycle from analysis to deployment while you focus on high-level strategy.

Integration and Feed Maintenance

`get_application_info` and `list_integrations` allow your monitor agents to verify the health of your external connections using the MCP standard. If an integration drops, the agent logs the failure and alerts your engineering team before data gets lost. Feed maintenance runs on autopilot. You can task a cleanup agent to regularly scan `list_push_messages` and execute `delete_event` on anything older than thirty days.

Setup guide

Set up Fomo MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Fomo tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Fomo Analyst",
    goal="Access and analyze Fomo data via MCP.",
    backstory="Expert analyst with direct Fomo access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Fomo transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Fomo Analyst",
        goal="Access and analyze Fomo data via MCP.",
        backstory="Expert analyst with direct Fomo access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Fomo transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Fomo. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Fomo MCP in CrewAI

Pass the server URL directly into your agent's `mcps` array. For granular control, use `MCPServerHTTP` from `crewai.mcp` and apply a tool filter.

Yes. You can use `tool_filter` to give your research agent access to `list_events` while only allowing the execution agent to run `create_event`.

The framework uses shared memory to pass context between agents. When one agent fetches template details, the next agent in the sequence can read that exact format without making another API call.

Yes. CrewAI handles the standard protocol communication under the hood. You just pip install the framework with tools enabled and pass the endpoint.

The server handles exact order values and geographic locations. CrewAI isolates tool execution within a zero-trust V8 sandbox, meaning your e-commerce data cannot leak into other agent memory spaces.

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