How to Use the Formbricks MCP in CrewAI

Q: How do I configure the Formbricks MCP Server in CrewAI?

Run pip install crewai "crewaitools". You can pass the HTTP transport URL directly into the mcps array on your Agent definition.

Q: Can I restrict which Formbricks tools a CrewAI agent uses?

Yes. You use MCPServerHTTP from crewai.mcp and apply a toolfilter. You can give the research agent read-only access while the manager agent gets creation rights.

Deploy a multi-agent CrewAI team to monitor, analyze, and act on Formbricks feedback.

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Connect Formbricks MCP to CrewAI

Create your Vinkius account to connect Formbricks 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 Formbricks with CrewAI

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Agentic Support Triage

A specialized research agent uses `list_responses` to constantly monitor incoming user feedback. You don't need a human reading every single form submission. The agent pulls the data, filters the noise, and passes the high-signal items to the next agent in the crew. The support agent takes over. It grabs the exact submission using `get_response` and drafts a personalized reply. Because CrewAI shares memory across the team, the second agent already knows the full context of the user's issue thanks to the MCP integration.

Survey Management MCP Server

Your operations crew manages the entire feedback lifecycle using `create_survey` and `delete_survey`. A product manager agent decides a feature needs testing. It spins up a new survey automatically. When the test concludes, a moderator agent cleans up. It calls the deletion tool to remove the stale survey from your app. You run these hierarchical operations in the background. The CrewAI MCP Server integration handles the API mechanics while your agents focus on the strategy.

User Context Retrieval

Before an agent replies to a complaint, it runs `get_person` to pull the user's history. It checks `list_people` to see if they belong to a larger account that's at risk of churning. The agent cross-references this profile against `list_action_classes` to see what the user actually clicked before they complained. You get a complete picture of the friction point. The crew formulates a fix and escalates it to your engineering team without human intervention.

Setup guide

Set up Formbricks 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 Formbricks tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

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

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

Run `pip install crewai "crewai[tools]"`. You can pass the HTTP transport URL directly into the `mcps` array on your Agent definition.

Yes. You use `MCPServerHTTP` from `crewai.mcp` and apply a `tool_filter`. You can give the research agent read-only access while the manager agent gets creation rights.

The framework excels at this. Agent A can fetch responses, Agent B can analyze them, and Agent C can trigger a webhook based on the findings.

The tool will return an error. You should configure a monitor agent to watch the session and correct invalid tool calls before they break the pipeline.

This integration touches direct user complaints and identifiable profile data via the `get_person` payload. CrewAI connects through an ephemeral V8 Isolate Sandbox. The zero-trust architecture ensures your customer feedback remains strictly bound to your authorized token.

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