How to Use the Culture Amp MCP in CrewAI

Q: How do I configure Culture Amp tools in CrewAI?

Pass your Vinkius MCP endpoint directly into the mcps array on your Agent definition. The framework automatically discovers all available operations.

Q: Can CrewAI agents filter Culture Amp data before acting?

Yes. You use the MCPServerHTTP class with a toolfilter to restrict exactly which endpoints an agent can see.

Deploy a crew of autonomous AI agents to monitor Culture Amp surveys and manage your employee directory with CrewAI.

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Connect Culture Amp MCP to CrewAI

Create your Vinkius account to connect Culture Amp 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 Culture Amp with CrewAI

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Perplexity

Build HR Teams in CrewAI

One agent cannot handle complex organizational analytics alone. You connect this MCP Server and assign a researcher agent to run `list_analytics_datasets` and find relevant reporting structures. A second analyst agent takes that context and queries `get_survey_details` to map participant counts. They share memory during the session, handing off data sequentially to build a complete picture of employee engagement.

Monitor Directory Changes via MCP Server

Keeping identity systems synchronized requires constant vigilance. You spin up a watcher agent that periodically executes `list_employees` to snapshot the directory boundary. When it detects a discrepancy, a moderator agent takes over. It uses `search_employees_by_name` to verify the missing profile and triggers `create_employee_record` to resolve the directory state without human input.

Map Complex Demographics Autonomously

Understanding how different teams respond to feedback requires deep data mapping. Your specialized mapping agent pulls metadata using `list_demographic_fields`. It then cross-references those identifiers against `list_organizational_groups`. The hierarchical classification feeds straight into your final report, completely bypassing manual data wrangling.

Setup guide

Set up Culture Amp 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 Culture Amp tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Pass your Vinkius MCP endpoint directly into the `mcps` array on your Agent definition. The framework automatically discovers all available operations.

Yes. You use the `MCPServerHTTP` class with a `tool_filter` to restrict exactly which endpoints an agent can see.

Agents maintain shared memory throughout the execution task. An analyst reads the exact dataset identifiers a researcher found earlier.

The Python implementation supports stdio, SSE, and Streamable HTTP. You define the URL and the underlying protocol handles the rest.

Vinkius manages all authentication at the endpoint level inside an ephemeral sandbox. Once your crew finishes analyzing the analytics data-source boundary, the MCP server environment is wiped clean.

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