How to Use the Measured MCP in CrewAI

Q: How do I assign Measured tools to specific agents in a CrewAI team?

Pass the server URL to the mcps array of your specific analyst agent. This ensures only that agent can call getcampaignperformance, keeping your other agents focused on strategy.

Q: Can a CrewAI agent access historical marketing reports from Measured?

Yes. An agent equipped with this toolset can call listreports to locate historical files, then use the metadata to analyze long-term marketing trends.

Q: How do CrewAI agents share data fetched from the Measured platform?

CrewAI has a shared memory system. When one agent runs getperformancebychannel, the resulting metrics are immediately available to other agents in the crew for further analysis.

Q: What happens if a CrewAI agent fails to fetch incrementality scores?

If getincrementalityscores fails due to network issues, CrewAI's execution loop retries the tool call. If the failure persists, the agent reports the error back to the manager agent.

Deploy specialized CrewAI marketing teams to analyze Measured incrementality and optimize channel spend.

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Connect Measured MCP to CrewAI

Create your Vinkius account to connect Measured 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 Measured with CrewAI

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Collaborative Marketing Analysis in CrewAI

This CrewAI setup lets you deploy specialized agents to analyze your marketing channels using the `list_channels` tool over an active MCP connection. One agent identifies the active ad networks, while a second agent evaluates their performance. The analyst agent calls `get_performance_by_channel` to gather specific metrics for each platform. Because CrewAI agents share memory, they collaborate to find underperforming channels without repeating API queries.

Autonomous Incrementality Audits with MCP Server

This Measured MCP Server enables your CrewAI team to audit marketing lift using `get_incrementality_scores`. An audit agent pulls the incrementality metrics, while a strategist agent compares them against overall spend. The strategist uses `get_insights` to identify where ad networks are taking credit for organic conversions. The crew then compiles a unified recommendation, saving your team hours of manual spreadsheet work.

Hierarchical Campaign Reporting

Set up a hierarchical CrewAI team where a manager agent coordinates reporting using `list_reports`. The manager delegates specific campaigns to subordinate agents, who fetch raw data using `get_campaign_performance`. The agents feed their findings into `get_performance_summary` to build a unified executive summary. That's how you prevent agents from making redundant API calls, keeping your execution fast.

Setup guide

Set up Measured 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 Measured tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass the server URL to the `mcps` array of your specific analyst agent. This ensures only that agent can call `get_campaign_performance`, keeping your other agents focused on strategy.

Yes. An agent equipped with this toolset can call `list_reports` to locate historical files, then use the metadata to analyze long-term marketing trends.

CrewAI has a shared memory system. When one agent runs `get_performance_by_channel`, the resulting metrics are immediately available to other agents in the crew for further analysis.

If `get_incrementality_scores` fails due to network issues, CrewAI's execution loop retries the tool call. If the failure persists, the agent reports the error back to the manager agent.

Your performance metrics and ROAS data remain secure because all tool execution happens in an ephemeral V8 sandbox. Vinkius handles the authorization token securely, so your raw marketing metrics are never exposed to public networks during multi-agent runs.

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