How to Use the Metricool MCP in CrewAI

Q: How do I pass Metricool tools to a CrewAI agent?

Pass your Vinkius MCP server URL directly into the agent's mcps list during initialization. CrewAI automatically discovers tools like getunifiedsummary and makes them available to that specific agent.

Q: How do I restrict which CrewAI agents can access Metricool?

Use the MCPServerHTTP class from crewai.mcp and apply a tool filter. This lets you restrict access so only your Analyst Agent can call sensitive tools like listmetricoolprofiles.

Deploy specialized teams of CrewAI agents to manage your Metricool publishing and analytics autonomously.

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Connect Metricool MCP to CrewAI

Create your Vinkius account to connect Metricool 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 Metricool with CrewAI

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Run a multi-agent social media newsroom

CrewAI lets you set up specialized roles that divide and conquer your social strategy. You can have an Analyst Agent pull data using `get_unified_summary` while a Strategy Agent reviews the output to suggest new content angles. This cooperative setup avoids the limits of a single agent. The specialized agents pass context back and forth, turning raw social metrics into actionable plans without human intervention.

Automated ad performance monitoring via CrewAI

Set up a dedicated monitor agent to keep your ad spend on track. The agent calls `get_ads_performance` to pull the latest cost-per-click metrics across your connected networks. If performance dips, the monitor agent passes the data to a manager agent. This allows your crew to flag issues or adjust budgets dynamically based on real-time returns.

Keep your publishing calendar organized with an MCP Server

Let your CrewAI team manage your queue directly. A writer agent drafts updates, a moderator agent approves them, and a publisher agent uses `get_social_planner` to schedule them. This structured workflow ensures every post is vetted before it goes live. You get automated scheduling with built-in quality control.

Setup guide

Set up Metricool 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 Metricool tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent Metricool 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="Metricool Analyst",
        goal="Access and analyze Metricool data via MCP.",
        backstory="Expert analyst with direct Metricool access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Metricool 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 Metricool. 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 Metricool MCP in CrewAI

Pass your Vinkius MCP server URL directly into the agent's `mcps` list during initialization. CrewAI automatically discovers tools like `get_unified_summary` and makes them available to that specific agent.

Yes, agents share access to the MCP server. Your Analyst Agent can pull data with `get_instagram_analytics` while your Scheduler Agent inspects the calendar using `get_social_planner`.

Use the `MCPServerHTTP` class from `crewai.mcp` and apply a tool filter. This lets you restrict access so only your Analyst Agent can call sensitive tools like `list_metricool_profiles`.

CrewAI agents execute tools based on their assigned tasks. To prevent your crew from hitting API limits when calling `list_published_posts`, configure task intervals or limit the number of loops allowed per agent.

All execution happens within Vinkius's ephemeral V8 sandboxes. Your social tokens and analytics data are processed strictly in memory and never exposed to the LLM provider or stored in CrewAI's local logs.

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